ELIGIBILITY:

Degree level: Postgraduate doctoral

Tuition fee status: Home, Overseas

Available to: Prospective students

Ideal candidates will have a strong interest in coding (Python), quantitative thinking, and machine learning, with motivation to apply these skills to protein and antibody design. Prior experience in ML is beneficial but not essential.

Please contact Professor Pietro Sormanni for further details—pietro.sormanni@imperial.ac.uk.

Start date: As soon as possible

Research themes include foundation models, multi-objective optimisation, active learning, and interpretable ML

Access to experimental datasets and modern ML frameworks

Collaborative, interdisciplinary lab environment with mentoring and opportunities to publish tools and datasets

Please note: This studentship is not available to continuing students.

If you have any additional questions, please contact us at pietro.sormanni@imperial.ac.uk.

BENEFIT:

Value: Fully funded studentship