President's PhD Scholarships

Imperial College London offers a wide range of research opportunities in AI for PhD candidates through its Department of Computing and several specialized Centres for Doctoral Training (CDTs). While PhD study is primarily research-based, these areas indicate where a student would focus their doctoral research.

Key areas covering AI research at Imperial College London include:

• Core Artificial Intelligence The Department of Computing has a strong focus on both the theoretical foundations and applications of AI. This includes expertise in:

  • Machine learning
  • Knowledge representation and reasoning
  • Autonomous agents and multi-agent systems
  • Human-machine interactions and collectives
  • Cognition and human modeling
  • Data science
  • Robotics
  • Augmented reality, graphics, computer vision, and imaging
  • Audio-visual signal processing, natural language processing, and affective computing

• Specialized Centres for Doctoral Training (CDTs) Imperial is home to several CDTs that provide structured training alongside PhD research in specific AI subfields:

  • UKRI Centre for Doctoral Training in AI for Healthcare (AI4Health): This CDT focuses on AI's application in healthcare, including interpretable AI, privacy-preserving learning, trust in AI, data-efficient learning, and safety in autonomy.
  • UKRI Centre for Doctoral Training in Safe & Trusted AI: Dedicated to training researchers in developing safe and reliable AI systems.
  • EPSRC CDT in Smart Medical Imaging: Concentrates on smart technologies for the entire medical imaging process.
  • EPSRC CDT in Modern Statistics and Statistical Machine Learning: Aims to train future leaders in statistics and statistical machine learning.

• Specific Research Groups and Initiatives

  • AI Security and Privacy Lab: Addresses privacy and safety concerns in AI, including synthetic data, large language models (LLMs), and agentic systems, often from an adversarial perspective.
  • Explainable AI: Researchers across the College work on developing AI systems whose decision-making processes are understandable to humans, crucial for trust and applications in sensitive domains.
  • Human-Like Computing Network+: Supports multidisciplinary research in human-like computing, including hybrid approaches combining statistical and symbolic machine learning.
  • Joint Academy of Doctoral Studies with TUM: A partnership with the Technical University of Munich focusing on "Artificial Intelligence, Healthcare and Robotics".

Prospective PhD students typically identify a research area and a supervisor within these departments and centers rather than enrolling in specific courses like a taught Master's program. You can explore the Department of Computing's website and the various CDT pages for more details on current research projects and faculty interests.