Studentship overview
Degree level
Postgraduate doctoral
Value
Fully funded studentship
Number of awards
1
Academic year
2026/2027
Tuition fee status
Home, Overseas
Mode of study
Full time
Available to
Prospective students
Application deadline
Additional information
Available to applicants in the following departments
- Chemical Engineering
Eligibility criteria
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 note: This studentship is not available to continuing students.
Course specific information
This PhD project is based in the Department of Chemical Engineering. It focuses on developing innovative AI methods to design therapeutic-grade antibody and protein sequences.
Application process
Please contact Professor Pietro Sormanni for further details - pietro.sormanni@imperial.ac.uk
Additional information
- 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
Contact
If you have any additional questions, please contact us at pietro.sormanni@imperial.ac.uk.