PhD Studentship: Identifying and processing information sources for medical applications under privacy and fairness constraints.

The School of Science and Technology, with its industrial partner 4BetterDevices GmbH, offers a studentship for the development of machine learning methods for feature selection and sensitivity analysis in biomedical data, in affiliation to the Artificial Intelligence Research Centre.

The successful candidate will develop statistical and machine learning techniques to analyse biomedical data. High-dimensional data sets are increasingly collected for medical diagnosis and in biological research and an important question regards characterising how information relevant for a certain medical purpose is distributed among the factors composing the data, and how to extract and use relevant information considering privacy and ethical constraints. The student will improve feature selection methods for medical diagnosis, and for the identification of nuisance features that may compromise privacy or introduce discriminatory biases. The student will also have the opportunity to apply these methods to better understand the distribution of information and the structure of representations in neural networks, advancing towards more transparent deep learning models for medical decision-making.

The student will acquire a robust foundation for an academic career and a set of skills highly appreciated in industry, with expertise in machine learning, statistical learning, deep learning, and data analysis. Starting date is July 2024, or October, at the latest. The position will remain open until filled.

Eligibility and requirements 

The candidate should have an upper second-class BSc/BEng/MSc/MEng (or equivalent, or higher) degree in Mathematics, Computer Science, Statistics, Engineering, Physics, or related STEM areas.

Scholarship: The studentship is for 3 years and will provide an annual tax-free stipend of £20,662/year and tuition fees (Home only). 

Additional income: There is the opportunity to earn around £2,200/year on an average (max. is around £4,300/year) through a teaching assistantship.

A candidate who demonstrates good aptitudes in machine learning, statistical modelling, or data analysis (as evidenced through strong academic credentials or research papers in reputable journals/conferences) may be accorded preference. Ideally, candidates should have proven skills in some of those areas and coding skills in Python and/or Matlab. 

A doctoral candidate is expected to meet the following pre-requisites: 

• Demonstrate a sound knowledge of their research area;
• Achieve and demonstrate significant depth in some chosen sub-areas relevant to their primary research area;
• Demonstrate the ability to conduct independent research, including a critical assessment of their own and others’ research.

If you are interested in applying, I, Dr Daniel Chicharro, will be happy to address any initial informal enquiries: Daniel.Chicharro@city.ac.uk

How to apply

To apply online click the 'Apply' button above.

When applying, specify the project you apply for writing the title or ‘supervisor Dr. Chicharro’

For queries regarding the application process, please contact pgr.sst.enquire@city.ac.uk

City, University of London is committed to promoting equality, diversity and inclusion in all its activities, processes, and culture for our whole community, including staff, students and visitors.

We welcome applications regardless of age, caring responsibilities, disability, gender identity, gender reassignment, marital status, nationality, pregnancy, race and ethnic origin, religion and belief, sex, sexual orientation and socio-economic background. City operates a guaranteed interview scheme for disabled applicants.

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