Research Scientist in AI for Healthcare

The post-holder will take a major role in the research activity of the CHI Lab within the Oxford Suzhou Centre for Advanced Research (OSCAR) site at Suzhou, China, under the overall supervision of Prof. David Clifton (https://eng.ox.ac.uk/people/david-clifton). Research will be undertaken in collaboration with clinical colleagues in the Oxford University Hospitals NHS Foundation Trust and other collaborators, including those based in China. 

OSCAR has a strong track record in commercialising its research outcomes, including the creation of spin-out/start-up companies. Research outcomes from the programmes on which the post-holder would work would be considered for licensing and spin-out activity as appropriate. OSCAR recognises researchers involved in such work via royalty streams, potential equity in resulting companies, etc. The work will comprise machine learning research for analysing large-scale clinical data, including time-series physiological data, blood test data, medications/interventions, and clinical diagnoses. 

The post would be suitable for applicants with general interests in AI, machine learning, large language models, foundation models, signal processing, computational statistics, and biomedical engineering.  The post will involve liaising closely with the Oxford-based lab, including exchange visits to Oxford. This post represents a uniquely promising career pathway, offering the post-holder the opportunity to advance to a postdoctoral researcher position at the CHI Lab, University of Oxford, and to bridge research experience between China and one of the world’s leading universities.

Responsibilities

1. Develop research questions within the field of computational health informatics, conduct individual research, analysing detailed and complex qualitative and/or quantitative data from a variety of sources, and generate original ideas by building on existing concepts.
2. Develop, establish, and pursue appropriate analytical protocols and techniques to support research.
3. Regularly write research articles at an international level for peer-reviewed journals, book chapters, and reviews. Present papers at national and international conferences, and lead seminars to disseminate research findings.
4. Agree clear task objectives, organise, and delegate work to other members of the team and coach other members of the group on specialist methodologies or procedures.
5. Carry out collaborative projects with colleagues in partner institutions, and research groups.
6. Use scientific equipment in a laboratory environment, especially pertaining to computational systems typically used for machine learning.
7. Undertake literature searches for the project where appropriate, and interpret and present the findings to the research team and other interested parties.
8. Keep informed of developments in the field of machine learning and its application to the problem domain.

Selection Criteria

Essential:

1. Hold a relevant Ph.D/D.Phil in AI, signal processing, or a cognate discipline; 
2. Strong publication record in machine learning, signal processing, computational statistics, or a cognate application area;
3. Possess specialist knowledge (sufficient to develop research projects and methodologies) in the fields of machine learning tools for analysing healthcare data;
4. Proven competence in mathematics and programming data analysis methods in Matlab or Python.    

Desirable:

1. An interest in the application area of healthcare. 
2. Experience in large language model and foundation models research.