Queen Mary University of London seeks top talent in AI, Machine Learning and Computer Science

Queen Mary University of London is renowned for its cutting-edge research, ranked 14th in the world and 5th in the UK for the quality of our research (THE World University Rankings 2024) and in the top 100 universities worldwide according to the US News & World Report rankings. 

Home to world-renowned researchers, Queen Mary University is now seeking to fill up to 30 new permanent academic positions for exceptional researchers and educators working in Artificial Intelligence (AI), Machine Learning (ML), or Computer Science.  

These roles are available at all academic levels, from lecturer to full professor, and cater to both research-focused and education-focused interests. The deadline for applications is September 29. For further information, visit our dedicated webpages.

Professor Wen Wang, Vice-Principal and Executive Dean for Science and Engineering at Queen Mary University, said: "Queen Mary University of London is going from strength to strength as we expand our team of talented individuals in AI and Computer Science. The University has a history of pioneering Computer Science, and our interdisciplinary research and collaboration have produced  breakthroughs in areas from AI for drug discovery and medical imaging, to plant biodiversity and quantum computing. These strategic hires will further strengthen our position as a global leader." 

 Professor Colin Bailey, President and Principal of Queen Mary University said: "We are at the vanguard of research, innovation and education in fields such as AI, machine learning and computer science, with academics in the Faculty working in conjunction with our Digital Economy University Research institute (DERI). We continue to invest in our world-leading research and education – including through strategic initiatives such as this one – to align with the demands of future students and to address the evolving challenges facing society. Our commitment to fostering a diverse and inclusive environment, coupled with our sustained growth, makes us an ideal destination for academics seeking to make a significant impact." 

The Faculty of Science and Engineering is on a rapid upward trajectory, with research income more than doubling in the past two years. Recognised globally, 97 per cent of its science and engineering research output was rated as internationally excellent in the last REF (2021).  Notably, the University’s  Engineering was ranked second in the UK for research quality, and its Computer Science and Informatics was ranked eighth overall, securing the first position for research impact. 

The University is also at the forefront of AI research, education and policy, convening global events such as at the recent UK AI Safety Summit, and as a member of the U.S. Department of Commerce's AI Safety Institute Consortium (AISIC). Its continuous innovation is evident in its vibrant AI research community and recent recognition in the Knowledge Exchange Framework, where it was placed in the top category – Very High Engagement – for ‘Research partnerships’, ‘Public and Community Engagement’, and ‘IP and Commercialisation’. In addition, Queen Mary Innovation supports Queen Mary University researchers to turn their innovations into successful businesses.  

The Faculty of Science and Engineering is now seeking talented individuals for up to 30 new permanent academic positions, integrating with our existing teams in the areas below. For more information on these opportunities, please visit our dedicated web pages. 

 

Applications of AI, Machine Learning and Computational Modelling   

• Genomics and Life Sciences   

• Drug Discovery and Medicinal Chemistry   

• Healthcare, Medical Imaging, and Medtech   

• Ecology, Conservation and Biodiversity   

• Materials Discovery   

• Transport, Sustainable Energy and Electronics   

• Creative Industries, Human Communication and Behaviour   

• Quantum Technology and Gravitational Waves  

  

Fundamentals of AI, Machine Learning and Computing   

• Mathematical Foundations, Risks and Opportunities of AI   

• Computer Science