The Doctor of Philosophy (PhD) in Artificial Intelligence is a research-intensive doctoral programme designed to advance knowledge in intelligent systems, machine learning, and data-driven technologies.
The programme focuses on developing advanced computational models, algorithms, and AI-driven solutions across industries such as healthcare, finance, robotics, and smart systems. Scholars engage in original research addressing complex real-world problems using artificial intelligence techniques.
Graduates are prepared for leadership roles in academia, research institutions, technology companies, and innovation-driven industries.
PhD in Artificial Intelligence scholars will be able to:
PA1 Conduct original research in artificial intelligence and intelligent systems.
PA2 Develop advanced machine learning models and AI algorithms.
PA3 Analyse large datasets to generate predictive and decision-making insights.
PA4 Apply AI techniques to solve complex interdisciplinary problems.
PA5 Uphold ethical standards in AI development and deployment.
Knowledge
1 Demonstrate advanced understanding of machine learning, deep learning, and neural networks.
2 Critically evaluate AI methodologies, models, and computational frameworks.
3 Understand data science, big data analytics, and intelligent automation systems.
4 Apply research methodologies in computer science and artificial intelligence.
Skills
1 Design and implement AI algorithms and intelligent systems.
2 Analyse and interpret complex datasets using advanced tools and techniques.
3 Develop innovative AI-based solutions for industry and research applications.
4 Communicate technical findings effectively to academic and professional audiences.
Competencies
1 Demonstrate leadership in AI research and technological innovation.
2 Manage complex research projects in artificial intelligence.
3 Contribute to advancements in automation, robotics, and data-driven technologies.
4 Present and defend research findings in academic and industry environments.
The PhD in Artificial Intelligence is designed to develop advanced research and technical capabilities through structured coursework and independent investigation.
Scholars are required to select a research topic, conduct a comprehensive literature review, develop AI models or frameworks, and produce a doctoral thesis of approximately 60,000–80,000 words.
The programme typically consists of 30–40% coursework and 60–70% research, with a final viva (oral defense) required for successful completion.
Assessment includes coursework, research projects, thesis submission, and viva defense.
The doctoral thesis must demonstrate originality, technical innovation, and a significant contribution to artificial intelligence and computational sciences.
Evaluation structure:
Dissertation Report – ⅔
Dissertation Defense – ⅙
Coursework / Publications – ⅙
An interim Master of Philosophy (MPhil) may be awarded upon successful completion of initial research stages and coursework, subject to institutional policies.
Ages 21 – 35
Ages 36 – 60
Ages 60+
- AI Research Scientist
- Machine Learning Engineer
- Data Scientist
- Robotics Engineer
- AI Consultant
- Academic Lecturer / Professor
Milestone 1:Research Foundation & Proposal Development |
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| AI 101: Advanced Machine Learning & Algorithms | ||
| AI 102: Research Methods & Ethics in AI | ||
| RES 101: Research Proposal Development | ||
Milestone 2:Advanced AI Research & Development |
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|---|---|---|
| AI 201: Deep Learning & Neural Networks | ||
| AI 202: Data Science & Big Data Analytics | ||
| RES 102: Academic Publications | ||
Milestone 3:Thesis Completion & Defense |
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|---|---|---|
| AI 301: Model Evaluation & Optimization | ||
| AI 302: Thesis Writing & Structuring | ||
| RES 103: Dissertation Submission & Viva | ||
Programmes are subject to periodic review. Modifications may be made to align with advancements in artificial intelligence, data science, and global technological standards.
For more details or admissions contact now!
Andrew Barrow
Head of Admission Department