Artificial intelligence research topics for phd manuscripts 2021, introduction.
Imagine a world where knowledge isn’t limited to humans!!! A world in which computers will think and collaborate with humans to create a more exciting universe. Although this future is still a long way off, Artificial Intelligence has made significant progress in recent years. In almost every area of AI, such as quantum computing, healthcare, autonomous vehicles, the internet of things, robotics, and so on, there is a lot of research going on. So much so that the number of annual Published Research Papers on Artificial Intelligence has increased by 90% since 1996.
Keeping this in mind, there are several sub-topics on which you can concentrate if you want to study and write a thesis on Artificial Intelligence. This article covers a few of these subjects and provides a short overview. Here some of the recent Research Topics ,
- Artificial Intelligence and Machine learning – Recent Trands
- How AI and ML can aid healthcare systems in their response to COVID-19
- Machine learning and artificial intelligence in haematology
- Tackling the risk of stranded electricity assets with machine learning and artificial intelligence
Deep Learning is a type of machine learning that learns by simulating the internal workings of the human brain in order to process data and make decisions.Deep Learning is a form of machine learning that employs artificial neural networks. These neural networks are linked in a web-like structure, similar to the human brain’s networks (basically a condensed version of our brain!).
Artificial neural networks have a web-like structure that allows them to process data in a nonlinear manner, which is a major advantage over conventional algorithms that can only process data in a linear manner. Rank Brain, one of the variables in the Google Search algorithm, is an example of a deep neural network.
Recent research topics
- Artificial intelligence & deep learning : PET and SPECT imaging
- Hierarchical Deep Learning Neural Network (HiDeNN): A computational science and engineering in AI architecture.
- AI for surgical safety: automatic assessment of the critical view of safety in laparoscopic cholecystectomy using Deep Learning
- Deep learning-enabled medical computer vision
Reinforcing Learning is an aspect of Artificial Intelligence in which a computer learns something in the same way as humans do. Assume the computer is a student, for example. Over time, the hypothetical student learns from its errors. As a outcome of trial and error, Reinforcement Machine Learning Algorithms learn optimal behaviour.
This means that the algorithm determines the next way to proceed by learning behaviours based on its current state that will increase the reward in the future. This also works for robots, just as it does for humans!
Google’s AlphaGo Computer Programme , for example, used Reinforcement Learning to defeat the world champion in the game of Go (a human!) in 2017.
- Experimental quantum speed-up in reinforcement learning agents
- Potential-based multiobjective reinforcement learning approaches to low-impact agents for AI safety
Robotics is an area concerned with the creation of humanoid robots that can assist humans and perform several acts. In certain cases, robots can behave like humans, but can they think like humans as well?
Kismet, a social interaction robot developed at M.I.T.’s Artificial Intelligence Lab, is an example of this. It understands human body language as well as our voice and responds to them appropriately. Another example is NASA’s Robonaut, which was designed to assist astronauts in space.
- Regulating artificial intelligence and robotics: ethics by design in a digital society
- Regional anaesthesia :usages of artificial intelligence and robotics in
- Third Millennium Life Saving Smart Cyberspace Driven by AI and Robotics
Natural Language Processing
Humans can obviously communicate with each other by speech, but now machines can as well! This is known as Natural Language Processing, and it involves machines analysing and understanding language and expression as it is spoken (which means that if you speak to a computer, it might only respond!). Speech recognition, natural language production, natural language translation, and other aspects of NLP are all concerned with language. NLP is recently very important in customer service applications, particularly chatbots. These chatbots use machine learning and natural language processing to communicate with users in textual form and respond to their questions. As a result, you get a personal touch in your customer service experiences without actually speaking with a human.
Here are several research papers in the field of Natural Language Processing that have been published. You can look at them to get more ideas for research and thesis topics on this subject.
- Natural Language Processing–Based Virtual Cofacilitator for Online Cancer Support Groups: Protocol for an Algorithm Development and Validation Study
- Sympathetic the temporal evolution of COVID-19 Research Through machine learning and natural language processing
The internet is full of images! This is the selfie age, and taking and posting a photo has never been easier. Each day, millions of images are uploaded to the internet and viewed. It’s important for computers to be able to see and understand images in order to make the most of the vast amount of images available online. And, while humans can do this without thinking about it, computers find it more difficult! This is where Computer Vision enters the image.
To extract information from images, Computer Vision utilizes Artificial Intelligence. This knowledge may include object detection in the image, image content recognition to group images together, and so on. Navigation for autonomous vehicles using images of the surroundings is one use of computer vision, such as AutoNav, which was used in the Spirit and Opportunity rovers that landed on Mars.
- Artificial intelligence for surgical safety: automatic assessment of the critical view of safety in laparoscopic cholecystectomy using deep learning
- An Open‐Source Computer Vision Tool for Automated Vocal Fold Tracking From Video endoscopy
Do you get movie and series recommendations from Netflix based on your previous choices or favourite genres? This is achieved by Recommender Systems, which offer you advice about what to do next from the vast array of options available online. Content-based Recommendation or even Collaborative Filtering may be used in a Recommender System.
The content of all the products is analysed in Content-Based Recommendation. For example, based on Natural Language Processing performed on the books, you might be recommended books that you may enjoy. Collaborative Filtering, on the other hand, analyses your past reading behaviour and then recommends books based on it.
- Artificial intelligence in recommender systems
- Deep Transfer Tensor Decomposition with Orthogonal Constraint for Recommender Systems.
- Recommender systems for configuration knowledge engineering
Internet Of Things
Artificial intelligence is concerned with the creation of systems that can learn to perform human-like tasks based on prior experience and without the need for human interaction. The Internet of Things, on the other hand, is a network of different devices linked to the internet and capable of collecting and exchanging data.
All of these IoT devices now generate a large amount of data, which must be collected and mined in order to produce actionable results. Artificial Intelligence enters the picture at this stage. The Internet of Things is used to collect and manage the massive amounts of data that Artificial Intelligence algorithms need. As a consequence, these algorithms transform the data into useful actionable results that IoT devices can use.
- Enhanced Medical Systems by using Artificial Intelligence and Internet of Things
- Artificial Intelligence and Internet of Things in Instrumentation and Control in Waste Biodegradation Plants: Recent Developments
- AIoT-Artificial Intelligence of Things
In this blog discussed the recent enhancement for artificial intelligences and their sub field. This will help to the PhD scholar who are interested to research in artificial intelligences domain.
- Shouval, R., Fein, J. A., Savani, B., Mohty, M., & Nagler, A. (2021). Machine learning and artificial intelligence in haematology. British journal of haematology, 192(2), 239-250.
- van der Schaar, M., Alaa, A. M., Floto, A., Gimson, A., Scholtes, S., Wood, A., … & Ercole, A. (2021). How artificial intelligence and machine learning can help healthcare systems respond to COVID-19. Machine Learning, 110(1), 1-14.
- Nyangon, J. (2021). Tackling the risk of stranded electricity assets with machine learning and artificial intelligence. In Sustainable Energy Investment-Technical, Market and Policy Innovations to Address Risk. IntechOpen.
- Saha, S., Gan, Z., Cheng, L., Gao, J., Kafka, O. L., Xie, X., … & Liu, W. K. (2021). Hierarchical Deep Learning Neural Network (HiDeNN): An artificial intelligence (AI) framework for computational science and engineering. Computer Methods in Applied Mechanics and Engineering, 373, 113452.
- Mascagni, P., Vardazaryan, A., Alapatt, D., Urade, T., Emre, T., Fiorillo, C., … & Padoy, N. (2021). Artificial intelligence for surgical safety: automatic assessment of the critical view of safety in laparoscopic cholecystectomy using deep learning. Annals of Surgery.
- Esteva, A., Chou, K., Yeung, S., Naik, N., Madani, A., Mottaghi, A., … & Socher, R. (2021). Deep learning-enabled medical computer vision. npj Digital Medicine, 4(1), 1-9.
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Artificial Intelligence Graduate Program
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"Artificial intelligence is the new electricity." Andrew Ng, Stanford Adjunct Professor
AI is changing the way we work and live, and has become a de facto part of business and culture. This graduate program, which has quickly become our most popular, provides you with a deep dive into the principles and methodologies of AI. Selecting from a variety of electives, you can choose a path tailored to your interests, including natural language processing, vision, data mining, and robotics.
Courses are taught by prominent Stanford faculty whose research is at the forefront of emerging AI developments, including Andrew Ng , Christopher Manning , Chelsea Finn , Percy Liang , Jeanette Bohg .
Required (complete at least 1)
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How Much It Will Cost
How long it will take.
- Complete four courses including 1-2 required course(s) and 2-3 electives within 3 academic years.
- Your time commitment will vary for each course. You should expect an average of 15-20 hours per week for the lecture and homework assignments.
- Most students complete the program in 1-2 years.
- CS229 is an especially difficult class. If you have never taken a graduate class through SCPD, we recommend choosing a different course to begin your studies.
What You Need to Get Started
Before enrolling in your first graduate course, you must complete an online application .
Don’t wait! While you can only enroll in courses during open enrollment periods, you can complete your online application at any time.
Once you have enrolled in a course, your application will be sent to the department for approval. You will receive an email notifying you of the department's decision after the enrollment period closes. You can also check your application status in your my stanford connection account at any time.
Learn more about the graduate application process .
What You'll Earn
Artificial Intelligence Graduate Certificate from Stanford University.
With each successful completion of a course in this program, you’ll earn Stanford University transcripts and academic credit, which may be applied to a relevant graduate degree that accepts these credits. You may transfer up to 18 units of these credits to an applicable Stanford University master’s degree (pending approval from the academic department.)
To earn the certificate, you will need to:
- Earn a grade of B (3.0) or better in each course
What You Need to Succeed
- College level calculus and linear algebra including a good understanding of multivariate derivatives and matrix/vector notation and operations (MATH104, MATH113, CS205L or equivalent).
- You should be familiar with Probability Theory and basic probability distributions (Continuous, Gaussian, Bernoulli, etc.) You should be able to define the following concepts for both continuous and discrete random variables; Expectation, independence, probability distribution functions, and cumulative distribution functions ( CS109 , STATS116 or equivalent).
- A conferred Bachelor’s degree with an undergraduate GPA of 3.0 or better.
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177 Great Artificial Intelligence Research Paper Topics to Use
In this top-notch post, we will look at the definition of artificial intelligence, its applications, and writing tips on how to come up with AI topics. Finally, we shall lock at top artificial intelligence research topics for your inspiration.
What Is Artificial Intelligence?
It refers to intelligence as demonstrated by machines, unlike that which animals and humans display. The latter involves emotionality and consciousness. The field of AI has gained proliferation in recent days, with many scientists investing their time and effort in research.
How To Develop Topics in Artificial Intelligence
Developing AI topics is a critical thinking process that also incorporates a lot of creativity. Due to the ever-dynamic nature of the discipline, most students find it hard to develop impressive topics in artificial intelligence. However, here are some general rules to get you started:
Read widely on the subject of artificial intelligence Have an interest in news and other current updates about AI Consult your supervisor
Once you are ready with these steps, nothing is holding you from developing top-rated topics in artificial intelligence. Now let’s look at what the pros have in store for you.
Artificial Intelligence Research Paper Topics
- The role of artificial intelligence in evolving the workforce
- Are there tasks that require unique human abilities apart from machines?
- The transformative economic impact of artificial intelligence
- Managing a global autonomous arms race in the face of AI
- The legal and ethical boundaries of artificial intelligence
- Is the destructive role of AI more than its constructive role in society?
- How to build AI algorithms to achieve the far-reaching goals of humans
- How privacy gets compromised with the everyday collection of data
- How businesses and governments can suffer at the hands of AI
- Is it possible for AI to devolve into social oppression?
- Augmentation of the work humans do through artificial intelligence
- The role of AI in monitoring and diagnosing capabilities
Artificial Intelligence Topics For Presentation
- How AI helps to uncover criminal activity and solve serial crimes
- The place of facial recognition technologies in security systems
- How to use AI without crossing an individual’s privacy
- What are the disadvantages of using a computer-controlled robot in performing tasks?
- How to develop systems endowed with intellectual processes
- The challenge of programming computers to perform complex tasks
- Discuss some of the mathematical theorems for artificial intelligence systems
- The role of computer processing speed and memory capacity in AI
- Can computer machines achieve the performance levels of human experts?
- Discuss the application of artificial intelligence in handwriting recognition
- A case study of the key people involved in developing AI systems
- Computational aesthetics when developing artificial intelligence systems
Topics in AI For Tip-Top Grades
- Describe the necessities for artificial programming language
- The impact of American companies possessing about 2/3 of investments in AI
- The relationship between human neural networks and A.I
- The role of psychologists in developing human intelligence
- How to apply past experiences to analogous new situations
- How machine learning helps in achieving artificial intelligence
- The role of discernment and human intelligence in developing AI systems
- Discuss the various methods and goals in artificial intelligence
- What is the relationship between applied AI, strong AI, and cognitive simulation
- Discuss the implications of the first AI programs
- Logical reasoning and problem-solving in artificial intelligence
- Challenges involved in controlled learning environments
AI Research Topics For High School Students
- How quantum computing is affecting artificial intelligence
- The role of the Internet of Things in advancing artificial intelligence
- Using Artificial intelligence to enable machines to perform programming tasks
- Why do machines learn automatically without human hand holding
- Implementing decisions based on data processing in the human mind
- Describe the web-like structure of artificial neural networks
- Machine learning algorithms for optimal functions through trial and error
- A case study of Google’s AlphaGo computer program
- How robots solve problems in an intelligent manner
- Evaluate the significant role of M.I.T.’s artificial intelligence lab
- A case study of Robonaut developed by NASA to work with astronauts in space
- Discuss natural language processing where machines analyze language and speech
Argument Debate Topics on AI
- How chatbots use ML and N.L.P. to interact with the users
- How do computers use and understand images?
- The impact of genetic engineering on the life of man
- Why are micro-chips not recommended in human body systems?
- Can humans work alongside robots in a workplace system?
- Have computers contributed to the intrusion of privacy for many?
- Why artificial intelligence systems should not be made accessible to children
- How artificial intelligence systems are contributing to healthcare problems
- Does artificial intelligence alleviate human problems or add to them?
- Why governments should put more stringent measures for AI inventions
- How artificial intelligence is affecting the character traits of children born
- Is virtual reality taking people out of the real-world situation?
Quality AI Topics For Research Paper
- The use of recommender systems in choosing movies and series
- Collaborative filtering in designing systems
- How do developers arrive at a content-based recommendation
- Creation of systems that can emulate human tasks
- How IoT devices generate a lot of data
- Artificial intelligence algorithms convert data to useful, actionable results.
- How AI is progressing rapidly with the 5G technology
- How to develop robots with human-like characteristics
- Developing Google search algorithms
- The role of artificial intelligence in developing autonomous weapons
- Discuss the long-term goal of artificial intelligence
- Will artificial intelligence outperform humans at every cognitive task?
Computer Science AI Topics
- Computational intelligence magazine in computer science
- Swarm and evolutionary computation procedures for college students
- Discuss computational transactions on intelligent transportation systems
- The structure and function of knowledge-based systems
- A review of the artificial intelligence systems in developing systems
- Conduct a review of the expert systems with applications
- Critique the various foundations and trends in information retrieval
- The role of specialized systems in transactions on knowledge and data engineering
- An analysis of a journal on ambient intelligence and humanized computing
- Discuss the various computer transactions on cognitive communications and networking
- What is the role of artificial intelligence in medicine?
- Computer engineering applications of artificial intelligence
AI Ethics Topics
- How the automation of jobs is going to make many jobless
- Discuss inequality challenges in distributing wealth created by machines
- The impact of machines on human behavior and interactions
- How artificial intelligence is going to affect how we act accordingly
- The process of eliminating bias in Artificial intelligence: A case of racist robots
- Measures that can keep artificial intelligence safe from adversaries
- Protecting artificial intelligence discoveries from unintended consequences
- How a man can stay in control despite the complex, intelligent systems
- Robot rights: A case of how man is mistreating and misusing robots
- The balance between mitigating suffering and interfering with set ethics
- The role of artificial intelligence in negative outcomes: Is it worth it?
- How to ethically use artificial intelligence for bettering lives
Advanced AI Topics
- Discuss how long it will take until machines greatly supersede human intelligence
- Is it possible to achieve superhuman artificial intelligence in this century?
- The impact of techno-skeptic prediction on the performance of A.I
- The role of quarks and electrons in the human brain
- The impact of artificial intelligence safety research institutes
- Will robots be disastrous for humanity shortly?
- Robots: A concern about consciousness and evil
- Discuss whether a self-driving car has a subjective experience or not
- Should humans worry about machines turning evil in the end?
- Discuss how machines exhibit goal-oriented behavior in their functions
- Should man continue to develop lethal autonomous weapons?
- What is the implication of machine-produced wealth?
AI Essay Topics Technology
- Discuss the implication of the fourth technological revelation in cloud computing
- Big database technologies used in sensors
- The combination of technologies typical of the technological revolution
- Key determinants of the civilization process of industry 4.0
- Discuss some of the concepts of technological management
- Evaluate the creation of internet-based companies in the U.S.
- The most dominant scientific research in the field of artificial intelligence
- Discuss the application of artificial intelligence in the literature
- How enterprises use artificial intelligence in blockchain business operations
- Discuss the various immersive experiences as a result of digital AI
- Elaborate on various enterprise architects and technology innovations
- Mega-trends that are future impacts on business operations
Interesting Topics in AI
- The role of the industrial revolution of the 18 th century in A.I
- The electricity era of the late 19 th century and its contribution to the development of robots
- How the widespread use of the internet contributes to the AI revolution
- The short-term economic crisis as a result of artificial intelligence business technologies
- Designing and creating artificial intelligence production processes
- Analyzing large collections of information for technological solutions
- How biotechnology is transforming the field of agriculture
- Innovative business projects that work using artificial intelligence systems
- Process and marketing innovations in the 21 st century
- Medical intelligence in the era of smart cities
- Advanced data processing technologies in developed nations
- Discuss the development of stelliform technologies
Good Research Topics For AI
- Development of new technological solutions in I.T
- Innovative organizational solutions that develop machine learning
- How to develop branches of a knowledge-based economy
- Discuss the implications of advanced computerized neural network systems
- How to solve complex problems with the help of algorithms
- Why artificial intelligence systems are predominating over their creator
- How to determine artificial emotional intelligence
- Discuss the negative and positive aspects of technological advancement
- How internet technology companies like Facebook are managing large social media portals
- The application of analytical business intelligence systems
- How artificial intelligence improves business management systems
- Strategic and ongoing management of artificial intelligence systems
Graduate AI NLP Research Topics
- Morphological segmentation in artificial intelligence
- Sentiment analysis and breaking machine language
- Discuss input utterance for language interpretation
- Festival speech synthesis system for natural language processing
- Discuss the role of the Google language translator
- Evaluate the various analysis methodologies in N.L.P.
- Native language identification procedure for deep analytics
- Modular audio recognition framework
- Deep linguistic processing techniques
- Fact recognition and extraction techniques
- Dialogue and text-based applications
- Speaker verification and identification systems
Controversial Topics in AI
- Ethical implication of AI in movies: A case study of The Terminator
- Will machines take over the world and enslave humanity?
- Does human intelligence paint a dark future for humanity?
- Ethical and practical issues of artificial intelligence
- The impact of mimicking human cognitive functions
- Why the integration of AI technologies into society should be limited
- Should robots get paid hourly?
- What if AI is a mistake?
- Why did Microsoft shut down chatbots immediately?
- Should there be AI systems for killing?
- Should machines be created to do what they want?
- Is the computerized gun ethical?
Hot AI Topics
- Why predator drones should not exist
- Do the U.S. laws restrict meaningful innovations in AI
- Why did the campaign to stop killer robots fail in the end?
- Fully autonomous weapons and human safety
- How to deal with rogues artificial intelligence systems in the United States
- Is it okay to have a monopoly and control over artificial intelligence innovations?
- Should robots have human rights or citizenship?
- Biases when detecting people’s gender using Artificial intelligence
- Considerations for the adoption of a particular artificial intelligence technology
Are you a university student seeking research paper writing services? We offer custom help for college students in any field of artificial intelligence.
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Doctor of Philosophy (PhD) in Artificial Intelligence
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Earn a doctorate degree in Artificial Intelligence, help lead innovation in a growing industry
The PhD in Artificial Intelligence is centered upon how computers operate to match the human decision making process in the brain. Your research will be led by AI experts with both research and industrial expertise. This emerging subject is starting to attract attention on the wider issues as the IOT and other advanced computer systems work in our lives.
This is a research based doctorate PhD degree where you will be assigned an academic supervisor almost immediately to guide you through your program and is based on mostly independent study through the entire program. It typically takes a minimum of two years but typically three years to complete if a student works closely with their assigned academic advisor. Under the guidance of your academic supervisor, you will conduct unique research in your chosen field before submitting a Thesis or being published in three academic journals agreed to by the academic supervisor. If by publication route it will require original contribution to knowledge or understanding in the field you are investigating.
As your PhD progresses, you move through a series of progression points and review stages by your academic supervisor. This ensures that you are engaged in a process of research that will lead to the production of a high-quality Thesis and/or publications and that you are on track to complete this in the time available. Following submission of your PhD Thesis or accepted three academic journal articles, you have an oral presentation assessed by an external expert in your field.
Click here to learn more about the Computer Science programs from the Chair of Computer Science, Dr. Robert Steele.
Learn around your busy schedule
Program is 100% online, with no on-campus classes or residencies required, allowing you the flexibility needed to balance your studies and career.
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Study at a university that specializes in industry-focused education in technology fields, with a faculty that includes many industrial and academic experts.
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Capitol’s doctoral programs are supervised by faculty with extensive experience in chairing doctoral dissertations and mentoring students as they launch their academic careers. You’ll receive the guidance you need to successfully complete your doctoral research project and build credentials in the field.
The PhD program offers 2 degree completion requirement options.
- Dissertation Option: the student will produce, present, and defend a doctoral dissertation after receiving the required approvals from the student’s Committee and the PhD Review Boards.
- Publication Option: the student will produce, present, and defend doctoral research that is published as articles (3 required) in high-impact journals identified by the university and the student’s Committee. Students must receive the required approvals from the student’s Committee and the PhD Review Board prior to publication.
Prior Achieved Credits May Be Accepted
Doctor of Philosophy - 60 credits
- Students will integrate and synthesize alternate, divergent, or contradictory perspectives or ideas fully within the field of Artificial Intelligence.
- Students will demonstrate advance knowledge and competencies in Artificial Intelligence.
- Students will analyze existing theories to draw data-supported consultations in Artificial Intelligence.
- Students will analyze theories, tools, and frameworks used in Artificial Intelligence.
- Students will execute a plan to complete a significant piece of scholarly work in Artificial Intelligence.
- Students will evaluate the legal, social, economic, environmental, and ethical impact of actions within Artificial Intelligence and demonstrate advance skill in integrating the results in to the leadership decision-making process.
Upon graduation, graduates will:
- integrate the theoretical basis and practical applications on Artificial Intelligence in to their professional work;
- demonstrate the highest mastery of Artificial Intelligence;
- evaluate complex problems, synthesize divergent/alternative/contradictory perspectives and ideas fully, and develop advanced solutions to Artificial Intelligence challenges; and
- contribute to the body of knowledge in the study of Artificial Intelligence.
Tuition & Fees
Tuition rates are subject to change.
The following rates are in effect for the 2022-2023 academic year, beginning in Fall 2022 and continuing through Summer 2023:
- The application fee is $100
- The per-credit charge for doctorate courses is $933. This is the same for in-state and out-of-state students.
- Retired military receive a $50 per credit hour tuition discount
- Active duty military receive a $100 per credit hour tuition discount for doctorate level coursework.
- High School and Community College full-time faculty and full-time staff receive a 20% discount on tuition for PhD or DSc programs.
For 2023-2024 doctorate tuition and fees, click here .
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8 Best Topics for Research and Thesis in Artificial Intelligence
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Imagine a future in which intelligence is not restricted to humans!!! A future where machines can think as well as humans and work with them to create an even more exciting universe. While this future is still far away, Artificial Intelligence has still made a lot of advancement in these times. There is a lot of research being conducted in almost all fields of AI like Quantum Computing, Healthcare, Autonomous Vehicles, Internet of Things , Robotics , etc. So much so that there is an increase of 90% in the number of annually published research papers on Artificial Intelligence since 1996. Keeping this in mind, if you want to research and write a thesis based on Artificial Intelligence, there are many sub-topics that you can focus on. Some of these topics along with a brief introduction are provided in this article. We have also mentioned some published research papers related to each of these topics so that you can better understand the research process.
So without further ado, let’s see the different Topics for Research and Thesis in Artificial Intelligence!
1. Machine Learning
Machine Learning involves the use of Artificial Intelligence to enable machines to learn a task from experience without programming them specifically about that task. (In short, Machines learn automatically without human hand holding!!!) This process starts with feeding them good quality data and then training the machines by building various machine learning models using the data and different algorithms. The choice of algorithms depends on what type of data do we have and what kind of task we are trying to automate. However, generally speaking, Machine Learning Algorithms are divided into 3 types i.e. Supervised Machine Learning Algorithms, Unsupervised Machine Learning Algorithms , and Reinforcement Machine Learning Algorithms.
2. Deep Learning
Deep Learning is a subset of Machine Learning that learns by imitating the inner working of the human brain in order to process data and implement decisions based on that data. Basically, Deep Learning uses artificial neural networks to implement machine learning. These neural networks are connected in a web-like structure like the networks in the human brain (Basically a simplified version of our brain!). This web-like structure of artificial neural networks means that they are able to process data in a nonlinear approach which is a significant advantage over traditional algorithms that can only process data in a linear approach. An example of a deep neural network is RankBrain which is one of the factors in the Google Search algorithm.
3. Reinforcement Learning
Reinforcement Learning is a part of Artificial Intelligence in which the machine learns something in a way that is similar to how humans learn. As an example, assume that the machine is a student. Here the hypothetical student learns from its own mistakes over time (like we had to!!). So the Reinforcement Machine Learning Algorithms learn optimal actions through trial and error. This means that the algorithm decides the next action by learning behaviors that are based on its current state and that will maximize the reward in the future. And like humans, this works for machines as well! For example, Google’s AlphaGo computer program was able to beat the world champion in the game of Go (that’s a human!) in 2017 using Reinforcement Learning.
Robotics is a field that deals with creating humanoid machines that can behave like humans and perform some actions like human beings. Now, robots can act like humans in certain situations but can they think like humans as well? This is where artificial intelligence comes in! AI allows robots to act intelligently in certain situations. These robots may be able to solve problems in a limited sphere or even learn in controlled environments. An example of this is Kismet , which is a social interaction robot developed at M.I.T’s Artificial Intelligence Lab. It recognizes the human body language and also our voice and interacts with humans accordingly. Another example is Robonaut , which was developed by NASA to work alongside the astronauts in space.
5. Natural Language Processing
It’s obvious that humans can converse with each other using speech but now machines can too! This is known as Natural Language Processing where machines analyze and understand language and speech as it is spoken (Now if you talk to a machine it may just talk back!). There are many subparts of NLP that deal with language such as speech recognition, natural language generation, natural language translation , etc. NLP is currently extremely popular for customer support applications, particularly the chatbot . These chatbots use ML and NLP to interact with the users in textual form and solve their queries. So you get the human touch in your customer support interactions without ever directly interacting with a human.
Some Research Papers published in the field of Natural Language Processing are provided here. You can study them to get more ideas about research and thesis on this topic.
6. Computer Vision
The internet is full of images! This is the selfie age, where taking an image and sharing it has never been easier. In fact, millions of images are uploaded and viewed every day on the internet. To make the most use of this huge amount of images online, it’s important that computers can see and understand images. And while humans can do this easily without a thought, it’s not so easy for computers! This is where Computer Vision comes in. Computer Vision uses Artificial Intelligence to extract information from images. This information can be object detection in the image, identification of image content to group various images together, etc. An application of computer vision is navigation for autonomous vehicles by analyzing images of surroundings such as AutoNav used in the Spirit and Opportunity rovers which landed on Mars.
7. Recommender Systems
When you are using Netflix, do you get a recommendation of movies and series based on your past choices or genres you like? This is done by Recommender Systems that provide you some guidance on what to choose next among the vast choices available online. A Recommender System can be based on Content-based Recommendation or even Collaborative Filtering. Content-Based Recommendation is done by analyzing the content of all the items. For example, you can be recommended books you might like based on Natural Language Processing done on the books. On the other hand, Collaborative Filtering is done by analyzing your past reading behavior and then recommending books based on that.
8. Internet of Things
Artificial Intelligence deals with the creation of systems that can learn to emulate human tasks using their prior experience and without any manual intervention. Internet of Things , on the other hand, is a network of various devices that are connected over the internet and they can collect and exchange data with each other. Now, all these IoT devices generate a lot of data that needs to be collected and mined for actionable results. This is where Artificial Intelligence comes into the picture. Internet of Things is used to collect and handle the huge amount of data that is required by the Artificial Intelligence algorithms. In turn, these algorithms convert the data into useful actionable results that can be implemented by the IoT devices.
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Best Doctorates in Artificial Intelligence: Top PhD Programs, Career Paths, and Salaries
The growing application of advanced technology in our daily lives has led to a high demand for professionals with qualifications in the field of artificial intelligence. The best PhDs in Artificial Intelligence offer tech professionals an opportunity to help meet this increased demand and land the highest-paying artificial intelligence jobs.
A careful look at some important factors for a PhD in Artificial Intelligence, such as program cost, length, and location, will help in determining the right artificial intelligence PhD program for you. This article also discusses some of the best artificial intelligence jobs and what you can expect to earn as a PhD in Artificial Intelligence salary.
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What Is a PhD in Artificial Intelligence?
A PhD in Artificial Intelligence is a doctorate program with an artificial intelligence research focus. Students are required to complete original research in various areas of applied artificial intelligence. These areas may include machine learning, artificial neural networks, speech recognition, and processing. PhD students will be assigned an academic advisor who will guide the student throughout their research.
How to Get Into an Artificial Intelligence PhD Program: Admission Requirements
The requirements to get into an artificial intelligence PhD program are a minimum of a Bachelor’s Degree in Computer Science or a related field, such as computer engineering, data science, or statistics. Students will also need a strong background in programming and system analysis, and fluency in several computer languages. There may also be course prerequisites in areas such as English, writing, deep learning, and neural cognitive modeling.
Further requirements may include transcripts of your undergraduate or graduate coursework and standardized tests scores such as the GRE. You may also be required to submit a statement of purpose that includes a description, proposal, or preliminary idea of your research areas of interest for your doctoral thesis.
PhD in Artificial Intelligence Admission Requirements
- Bachelor’s or master’s degree
- Letters of recommendation
- Statement of purpose
- Standardized test scores
- Strong background in programming languages such as Python and Java
- Knowledge of artificial intelligence subjects such as deep learning, neural and cognitive modeling, or computing
Artificial Intelligence PhD Acceptance Rates: How Hard Is It to Get Into a PhD Program in Artificial Intelligence?
It can be hard to get into a PhD program in Artificial Intelligence. Some programs are highly selective, and acceptance is not always based on merit alone. However, acceptance into some PhD programs is relatively easy if you meet all of the admissions requirements.
How to Get Into the Best Universities
Best PhDs in Artificial Intelligence: In Brief
Best universities for artificial intelligence phds: where to get a phd in artificial intelligence.
The best universities for artificial intelligence PhDs are Arizona State University, Syracuse University, and Drexel University. They have some of the best artificial intelligence laboratories, high acceptance rates, and the right networks of people. Below is a detailed list of the best schools to get a PhD in Artificial Intelligence.
Arizona State University was founded on March 12, 1885. It is a public research institution that offers various programs at the graduate level including business administration, economics, and computer science. The graduate programs of Arizona State University are well known for their first-class facilities as well as renowned researchers.
PhD in Computer Science
This PhD program at Arizona State University requires 84 credit hours, a written comprehensive exam, an oral comprehensive exam, a prospectus, and a dissertation. The university has an artificial intelligence laboratory where students can conduct research. Some of the topic areas include artificial intelligence, big data, statistical modeling, cloud computing, social computing, data mining, and machine learning.
PhD in Computer Science Overview
- Program Length: Approx. 5 years
- Acceptance Rate: N/A
- Tuition: $11,720/year (in state); $23,544/year (out of state)
- PhD Funding Opportunities: Awards and fellowships, graduate appointments, distinguished wards
PhD in Computer Science Admission Requirements
- Minimum GPA of 3.5 in last 60 hours of bachelor’s degree or in master’s degree overall
- 3 letters of recommendation
- Curriculum vitae or resume
- Proof of English proficiency
Capitol Technology University is a private research institution founded on June 1, 1927. It is best known for its proven academic excellence, as well as expert guidance in doctoral research. Capitol Technology University offers graduate programs in areas such as aeronautical science, cyber security, business analytics, data science, and computer science.
PhD in Artificial Intelligence
About 60 credits of coursework are required for the PhD in Artificial Intelligence at Capitol Technology University. The program emphasizes the principles of autonomous systems and expounds on how computers operate to match the human-like operation of computers for decision-making and problem-solving processes. The program is available both online and in person.
PhD in Artificial Intelligence Overview
- Program Length: Approx. 3 years
- Tuition: $933/credit
- PhD Funding Opportunities: Hometown Heroes discounts, EdAssist partner discounts, loans
PhD in Artificial Intelligence Admission Requirements
- Master’s degree in a relevant field
- 5 years of work experience
- Application letter
- Application fee: $100
- Official transcripts
- 2 letters of recommendation
Cornell University's main campus in Ithaca was founded in 1865 by Ezra Cornell and Andrew Dickson White. It is divided into seven undergraduate campuses and seven graduate divisions. Its computer science PhD program is ranked in the top six of such programs in the nation by US News & World Report, and it performs studious and academically-tasking research.
This program is designed for students with a particular interest in the general components of computing processes. Some study areas students can choose to specialize in include artificial intelligence, machine learning, data structures, robotics, natural language processing, quantitative analysis, programming languages and methodology, robotics, and theory of computation.
- Program Length: 4 - 6 years
- Tuition and Fees: $29,500/year
- PhD Funding Opportunities: Teaching assistantships, research assistantships, fellowships, loans
- Application fee of $105
- Undergraduate degree
- Official transcripts
- English language proficiency (for international applicants)
Drexel University offers research and professional degree programs in the arts and sciences, biomedical engineering, education, science and health systems, business, computing, and informatics. Drexel University graduate programs are well known for their flexibility.
Students in this program carry out in-depth and creative research. They may choose from areas such as artificial intelligence, computer vision, human-computer interaction, information assurance, and security research areas. Whatever the path they choose to specialize in, they must meet specified course requirements including 18 credits in computer science courses.
- Program Length: Within 7 years
- Tuition: $1,342/credit
- PhD Funding Opportunities: Private scholarships, student loans, Drexel Dean’s Fellowship, and research, teaching, and graduate assistantships
PhD in Computer and Information Science Admission Requirements
- Official final transcripts from all colleges/universities attended
- Official GRE scores
- Essay/statement of purpose
- Current resume
- Official TOEFL scores (international applicants)
Founded in 1868, Oregon State University is the largest public research university in the state with students from over 100 countries. It offers more than 80 graduate programs in fields such as AI, bioengineering, mechanical engineering, and biological and ecological engineering. It is well known for its abundant learning resources that aid students' research.
PhD in Artificial Intelligence and Robotics
This artificial intelligence and robotics PhD program teaches the theories, algorithms, and systems for making intelligent decisions in complex and uncertain environments. Students can explore research areas like perception and interpretation of sensor data, automated planning and reasoning, and human-machine interaction.
PhD in Artificial Intelligence and Robotics Overview
- Tuition: $557/credit (in state); $1,105/credit (out of state)
- PhD Funding Opportunities: Graduate, teaching, and research assistantships, graduate diversity recruitment bonus program
PhD in Artificial Intelligence and Robotics Admission Requirements
- Application fee
- Statement of objectives
- Graduate/undergraduate transcripts
- GPA of 3.00
Pace University was founded in 1906 as a business school by St. Clair Pace and Charles A. Pace. It has a main campus in New York City and secondary campuses in Westchester County, New York. It offers PhD programs in clinical psychology, computer science, mental health counseling, nursing, and school psychology.
Only students with demonstrated field experience are accepted into this extremely selective program. Students are closely involved in vital, strategic advanced research projects and make authentic advances in the field in areas such as pattern recognition in medical image segmentation, artificial intelligence, and intelligent systems. Each student is expected to pass three qualification exams.
- Program Length: 3 years
- Tuition: $1,420/credit
- PhD Funding Opportunities : Graduate assistantships, federal work-study, student loans
- Master’s Degree in Computer Science or a related field
- Research presentation
- $70 application fee
- Personal statement
- All official post-secondary transcripts
Syracuse University was founded on March 24, 1870. It offers over 200 graduate programs in fields such as data and research, computer science, and engineering, among others. It is well known for its professional programs, investment in research and innovation, and solid reputation.
PhD in Computer and Information Science and Engineering
The PhD in Computer and Information Science and Engineering program offered at Syracuse University is a well-structured program. Graduate students must complete a minimum of 48 credits in technical graduate courses, as well as other research courses.
In addition, each student must complete at least four credits of professional development courses. A proposal and a dissertation must also be completed and defended by the students.
PhD in Computer and Information Science and Engineering Overview
- Program Length: Within 5 years
- Acceptance Rate: 14.3%
- Tuition: $1,802/credit
- PhD Funding Opportunities: Teaching, research, and graduate assistantships, scholarships, university fellowships, research excellence doctoral funding programs
PhD in Computer and Information Science and Engineering Admission Requirements
- Bachelor’s or Master’s Degree in Computer Engineering, Computer and Information Science, or a related field
- TOEFL score (international applicants)
The University of Colorado is a public research institution located in Boulder, Colorado. It offers over 124 graduate and professional degrees in the arts and sciences, business, education, engineering, law, and music. The university allows students to collaborate with esteemed faculty and researchers and gain world-class expertise in their chosen fields.
This PhD in Computer Science at the University of Colorado requires 30 hours of graduate-level coursework, as well as 30 hours of thesis work. It also requires the completion of a preliminary exam, comprehensive exam, and dissertation defense, typically within six years of beginning your coursework.
- Program Length: Within 6 years
- Tuition: $780/credit (in state); $847/credit (out of state)
- PhD Funding Opportunities: Assistantships, fellowships, faculty research grants
- At least 3 courses in computer science beyond the introductory level
- Research experience
- Resume with research and publication details
- Copy of transcripts for the required undergraduate degree or master's degree
- Proof of financial support and a funding plan
Founded on August 26, 1817, the University of Michigan is known as one of the first public universities in the nation. It is ranked as the ninth best school for artificial intelligence by US News & World Report. The school offers master’s and PhD programs in areas like aerospace engineering, architecture, urban planning, and dentistry.
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PhD in Computer Science and Engineering
Intended for students who wish to pursue research or careers as postsecondary teachers, this PhD program is highly recognized for its offerings in relatively broad fields of knowledge. It is known for imparting a demonstrated ability in its graduates to carry out independent research, yielding significant original results.
PhD in Computer Science and Engineering Overview
- Program Length: 4 - 5 years
- Acceptance Rate: 1%
- Tuition and Fees: $14,558/full term (resident); $27,023/full term (nonresident)
- PhD Funding Opportunities: Graduate research assistantships on research grants and contracts, teaching assistantships
PhD in Computer Sciences and Engineering Admission Requirements
- Master's or bachelor's degree in any related field
- GPA of at least 3.5
- 3 strong letters of recommendation
- Proof of English proficiency (international students)
With over 11,000 graduate students enrolled, the University of Texas ranks among the 10 best public universities in the country, by US News & World Report. It offers graduate programs in various fields such as accounting, business, engineering, education and development, and computer science.
This program provides cutting-edge research experience as well as expertise in advanced computer science subjects. Through this program, students can specialize in the artificial intelligence track and conduct their research work on topics like information security, computer architecture, assistive technology, computer networks, and deep learning.
- Program Length: Within 8 years
- Tuition and Fees: $347.53/credit (in state); $1,344.63/credit (out of state)
- PhD Funding Opportunities: Grants and loans; department, institutional, and external fellowships and scholarships; research, teaching, and graduate assistantships
PhD in Computer Science Admission Requirements
- Transcripts of an ABA, BS, or MS degree in Computer Science/related area
- Completed graduate school application
- Resume/curriculum vitae
Can You Get a PhD in Artificial Intelligence Online?
Yes, you can get a PhD in Artificial Intelligence online. Some universities in the United States offer online artificial intelligence doctorate programs, like Capitol Technology University. The amount of time required to complete the online artificial intelligence program is about the same as the in-person program, depending on the institution.
Best Online PhD Programs in Artificial Intelligence
How long does it take to get a phd in artificial intelligence.
It takes about three to five years to get a PhD in Artificial Intelligence. That duration may be longer for people with particularly lengthy or complex research work or for those working part-time toward their PhD.
The reason for the longer duration could be a result of the institution’s requirements, the amount of research required before a thesis can be submitted, a student’s cooperation with their academic supervisor, or the program’s format, that is, whether it is full-time or part-time.
Is a PhD in Artificial Intelligence Hard?
No, a PhD in Artificial Intelligence is not that hard. Getting a PhD in computer-related programs can indeed be difficult, but when compared with other fields of theoretical study in computer science, a PhD in Artificial Intelligence is relatively easier.
PhD programs are very research-focused. What makes the PhD in Artificial Intelligence easier is that more emphasis is placed on empirical evaluation than on performance. That is, you have to prove that your method makes sense intuitively, not that it actually works. For your AI PhD, you can even show how an already established method works in a new area.
How Much Does It Cost to Get a PhD in Artificial Intelligence?
It costs about $19,792 per year to get a PhD in Artificial Intelligence , according to the National Center for Education Statistics. This average varies depending on the type of university involved. For public institutions, annual tuition averages about $12,410, while private universities charge about $26,597 per year. These rates are for in-state students only.
It is important to note that additional fees and costs also apply, such as application fees and department fees. However, most PhD programs have guaranteed financial support, although it doesn’t usually cover the entire cost of the degree.
How to Pay for a PhD in Artificial Intelligence: PhD Funding Options
Some of the PhD funding options available for students include research assistantships, where PhD students assist a member of faculty with their research. Students can also participate in a teaching assistantships, where they assist a professor in various academic-related areas. Instead of being paid for their work, students receive partial or full tuition or a stipend.
Another option for PhD funding is tuition waivers, which are awarded based on things like merit, race, or occupation. There also may be financial scholarships or loans available to help with costs.
Best Online Master’s Degrees
What Is the Difference between an Artificial Intelligence Master’s Degree and PhD?
One difference between an artificial intelligence master’s degree and a PhD is that a master’s degree program consists mostly of classwork and projects, with little intensive research work, while a PhD in Artificial Intelligence predominantly involves intensive research work aimed at finding answers and solutions to existing questions and problems.
It is harder to get a PhD than a master’s degree . In the field of artificial intelligence, master’s students will focus on multiple areas of learning, such as building multi-agent systems, economic systems, or artificial agents. PhD students will be more focused on solving a specific issue, requiring intense focus and strong critical-thinking and problem-solving skills, and making advancements in the field.
Master’s vs PhD in Artificial Intelligence Job Outlook
There is a difference in the job outlook for AI master’s degree holders and AI PhD holders. Those with a PhD in Artificial Intelligence have more job opportunities overall and can expect a higher salary than those with a Master’s Degree in Artificial Intelligence.
Some examples of jobs in artificial intelligence that require a PhD are big data engineer and architect, research scientist, natural language processing engineer, software architect, senior software engineer, and machine learning engineer. Those requiring a master’s degree include computer and information research scientist, data analyst, and artificial intelligence developer.
Difference in Salary for Artificial Intelligence Master’s vs PhD
A PhD in Artificial Intelligence is a terminal degree that brings with it higher salaries than a Master’s in Artificial Intelligence does. Someone with a PhD in the field of artificial intelligence earns about $115,000 per year, according to PayScale.
On the other hand, an artificial intelligence master’s degree holder earns $102,000 per year on average. This means that those with an AI PhD can expect to make about $13,000 more every year than those with an AI master’s degree.
Related Artificial Intelligence Degrees
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Why You Should Get a PhD in Artificial Intelligence
You should get a PhD in Artificial Intelligence because it opens the door to more employment opportunities and higher salaries. If you’re already employed, you may be able to keep your job for part or even all of your PhD program. Artificial intelligence is a growing and in-demand field, so obtaining the highest level of education will set you up for continuous opportunities.
Reasons for Getting a PhD in Artificial Intelligence
- More employment opportunities. With a PhD in Artificial Intelligence, landing a good job shouldn’t be a problem. The degree opens the door to more and better career opportunities.
- High-paying jobs. A Doctorate in Artificial Intelligence brings with it not only more career opportunities but also better salaries. PayScale shows that the average salary of a PhD degree holder in the field of artificial intelligence is about $115,000. However, the earning potential with this degree is considerably higher, as much as $200,000 per year for positions like principal scientist.
- Expertise in a versatile field. A doctorate degree in artificial intelligence will provide you with a deep understanding of AI theories and strong technical skills, which you can use to help solve future problems in a wide variety of fields.
- Plentiful research opportunities. With a PhD in Artificial Intelligence, you have the opportunity to engage in numerous research projects, which will increase your overall knowledge in the AI field and imbue you with the ability to find solutions to a wide variety of problems.
Getting a PhD in Artificial Intelligence: Artificial Intelligence PhD Coursework
Getting a PhD in Artificial Intelligence requires significant coursework in addition to the research element of the degree. Some common course topics include advanced data structures and algorithms, natural language learning, intermediate statistics, machine learning in practice, and regression analysis.
Foundations of Machine Learning
This course aims to teach students the founding principles of machine learning, its theory, and the techniques involved. The course includes different categories of machine learning including supervised learning, unsupervised learning, and reinforcement learning.
Advanced Data Structures and Algorithms
Through this course, students learn the branches of data science and how data is managed and organized to make it easily accessible. The knowledge gained from this course will equip the student with the skills needed for developing effective and useful software designs and algorithms.
This course teaches students how to use matrix algebra in experimental design. Students learn how to analyze complex data and use linear algebra to explore theories that involve two or more matrices. This skill is very useful when conducting research.
Probability and Random Variables
The course on probability and random variables in the field of artificial intelligence aims to teach PhD students how to reduce uncertainty when there is a margin of error as a result of the inadequacy of perfect information.
Machine Learning in Practice
In this course, students will put all that they have learned in the machine learning field into practice. They will apply their skills and knowledge in the areas of mathematics, computing, engineering, and data analysis to real-world datasets and examples.
Best Master’s Degrees
How to Get a PhD in Artificial Intelligence: Doctoral Program Requirements
To get a PhD in Artificial Intelligence, students must meet specific criteria that vary with each school and program. Some of the more common ones include a competency requirement, a project requirement, a breadth requirement, a teaching requirement, and approval of the thesis. Students also need to pass the necessary examinations before a PhD in Artificial Intelligence can be awarded.
Students are expected to demonstrate competency in various branches of artificial intelligence and all the theories taught in the program. They are also required to perform well on their examinations, usually with a grade of B+ or higher.
PhD students are required to take a specific number of upper-level courses for their degree. These courses need to encompass the different areas of artificial intelligence as well as the research problems and techniques associated with them.
As a way of showcasing the skills they have gained in their years of doctorate studies, PhD students must create and complete a project that’s in harmony with the project requirements of their particular program. This project will be based in a specialized field of artificial intelligence and must be approved by the project supervisors before this requirement can be met.
It is a requirement for PhD students to serve in the position of teaching assistant for at least two semesters or teach a course in their field for at least a semester. These roles allow PhD students to interact with students, sharpening their communication skills and preparing them for a possible career in academics.
Before a PhD in the field of artificial intelligence can be awarded, thesis research will be required of the PhD student. The thesis usually focuses on answering industry-wide problems. Once the thesis has been approved by the school supervising committee, then a doctoral degree in artificial intelligence can be given.
Potential Careers with an Artificial Intelligence Degree
PhD in Artificial Intelligence Salary and Job Outlook
The job outlook for artificial intelligence PhD holders is very good, as we are living in a time of rapid technological advancements. The US Bureau of Labor Statistics (BLS) predicts a growth of 22 percent in jobs like computer and research scientist through 2030. With an average salary of $115,000 for AI PhD holders, as stated above, you can expect to earn a great salary with your degree.
What Can You Do With a PhD in Artificial Intelligence?
With a PhD in Artificial Intelligence, you can get employed by top tech companies and work on a broad array of AI applications, programs, and systems. These include facial-recognition software, self-driving cars and drones, digital personal assistants, and more. AI students gain employment as computer scientists, AI experts, machine learning engineers, computational linguists, and robotics engineers after graduation. Here are some of the best jobs for artificial intelligence PhD holders.
Best Jobs with a PhD in Artificial Intelligence
- Big Data Engineer/Architect
- Software Architect
- Machine Learning Engineer
- Software Engineer
- Data Scientist
What Is the Average Salary for a PhD in Artificial Intelligence?
The average salary for a graduate with a PhD in Artificial Intelligence is $115,000 , according to PayScale. The exact salary you can expect will depend on a wide range of factors, which include your job title and responsibilities, the industry in which you are employed, your specific experience and knowledge, and the company’s geographic region.
Highest-Paying Artificial Intelligence Jobs for PhD Grads
Best artificial intelligence jobs with a doctorate.
The best artificial intelligence jobs with a doctorate degree are software architect, big data engineer/architect, machine learning engineer, data scientist, and software engineer. According to BLS, AI is taking a bigger role in our security , which will lead to even more job prospects in the field.
An artificial intelligence researcher conducts research to create and design new and better ways of solving problems. The models they create are used by data scientists to solve the real-world problems they were designed to solve.
- Salary with an Artificial Intelligence PhD: $131,490
- Job Outlook: 22% job growth from 2020 to 2030
- Number of Jobs: 33,000
- Highest-Paying States: Oregon, Arizona, Texas
Using their experience and research in artificial intelligence and software development, software engineers are capable of leading major software development projects. They can work for big IT companies such as IBM, Intel, Microsoft, and Alphabet.
- Salary with an Artificial Intelligence PhD: $126,668
- Number of Jobs: 1,847,900
- Highest-Paying States: Washington, California, New York
Engineers who work in machine learning are at the crossroads of software design and data science. They use big data technologies and programming structures to build production-ready, flexible, scalable models that can manage terabytes of actual data.
- Salary with an Artificial Intelligence PhD: $112,567
A robotics engineer is in charge of designing robots and robotic systems. With the implementation of AI, they will focus on designing complex robotic communication systems software and hardware components.
- Salary with an Artificial Intelligence PhD: $95,300
- Job Outlook: 7% job growth from 2020 to 2030
- Number of Jobs: 299,200
- Highest-Paying States: New Mexico, Louisiana, District of Columbia
Computational linguists’ job is to make communication possible between humans and machines by teaching computers how to understand us. They have a complex understanding of various programming languages and perform product-specific research in computational linguistics.
- Salary with an Artificial Intelligence PhD: $83,335
Is a PhD in Artificial Intelligence Worth It?
Yes, a PhD in Artificial Intelligence is worth it. Artificial intelligence and cognitive technology are expected to be the catalyst for the next scientific revolution. In a data-rich world, creating AI technology that can learn via developing and drawing conclusions based on human behavior could change the future and offer limitless industrial, social, and scientific possibilities.
As the world becomes more dependent on advancing technologies and intelligent machines, there is an ever-growing market for PhD holders in the field of artificial intelligence. A PhD in Artificial Intelligence will provide you with expertise in the field and qualify you for high demand careers in the field.
Additional Reading About Artificial Intelligence
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PhD in Artificial Intelligence FAQ
A PhD in Artificial Intelligence offers numerous lucrative career opportunities such as robotics engineer, senior software engineer, and machine learning expert. You will also be qualified to teach in a postsecondary institution.
The best places to pursue a PhD in Artificial Intelligence are accredited universities and colleges. Some of the top such institutions in the US include Arizona State University, Drexel University, and Syracuse University.
For students interested in a career in artificial intelligence, a computer science doctoral degree is a popular option. Many colleges and universities offer computer science doctorate programs with a focus on artificial intelligence or machine learning.
Because artificial intelligence is still a relatively new field, it’s difficult to know exactly how profitable the AI sector is. The value of artificial intelligence to the global economy will be $13 trillion by 2030, according to a report by the European Parliament. The world’s growing dependency on technological innovations and intelligent machines indicates that more growth is coming in this field.
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