About the Project
The Sormanni Lab develops data-driven technologies for rational antibody and protein design, combining artificial intelligence with laboratory directed evolution and biophysics to create new or improved antibodies and proteins. We build open, usable tools and validate designs through experiments and iterative design–build–test cycles, in our own lab and with academic and industrial partners (more info about the lab: www-sormanni.ch.cam.ac.uk).
We have openings across two complementary directions, and there is genuine scope for each student to shape their project within the group's broader aims.
Direction 1 – Methods development (computational). Developing AI methods that design therapeutic-grade antibody and protein sequences. Possible areas include:
- repertoire and structure-aware models
- multi-agentic workflows to perform automated or semi-automated designs rounds
- multi-objective optimisation across affinity, stability, solubility and immunogenicity
- active-learning loops that feed experimental measurements back into design;
- interpretable models that expose sequence–structure–function relationships.
Work is in Python and modern ML frameworks, with access to experimental datasets generated in-house and with partners as well as high-performance computing within the group, College, and National Facilities.
Direction 2 – Applications (lab-based and computational). Applying our design technologies to targets that have resisted conventional discovery but matter therapeutically or diagnostically – for instance membrane proteins, conformational or post-translationally modified epitopes, intracellular targets, or antigens for which no useful binder yet exists. The work couples computational design with in vitro display selection, expression and purification, biophysical characterisation of binding and stability, and developability assessment. Here in particular we welcome students who wish to propose the disease or target area they care most about; we will establish collaborations with experts in that area to steer the project and provide the biological context and assays that make the result meaningful.
What we offer
- A collaborative, multidisciplinary environment with access to HPC/GPU computation and a state-of-the-art biophysics lab.
- Supervision and mentoring with room to shape your project, and collaborations built around relevant application areas.
- Opportunities to publish tools, datasets and methods, and to work with industry and academic collaborators.
- Training in techniques you do not yet know, computational or experimental, tailored to your background.
What we expect
- For computational projects: enjoyment of coding (Python) and quantitative thinking, with an interest in proteins and antibodies. Prior ML experience is welcome but not essential.
- For lab-based projects: experience in or strong interest in molecular biology and protein work, and enthusiasm for data analysis and basic programming.
- For all projects: curiosity, rigour, clear communication, willingness to work outside your comfort zone, and the drive to become an independent scientist working in a multidisciplinary group.
How to apply
via Imperial's portal: https://www.imperial.ac.uk/study/apply/postgraduate-doctoral/application-process/ Select Department of Chemical Engineering and list Pietro Sormanni as supervisor. Enter “departmental PhD scholarship’ under name of scholarship, and select ‘Imperial’ under the scholarship dropdown, followed by ‘not sure’ under award amount. Indicate in your cover letter (or the relevant text field) which of the two directions you are more interested in. Submit the documents requested on the Imperial page.
This scholarship is open to all applicants regardless of their fee status. It covers both tuition fees and a tax-free contribution to maintenance costs of £25,000 per annum for 42 months.
The Department of Chemical Engineering at Imperial College London offers an advanced 3-4-year research degree that provides in-depth specialist training and knowledge in a topical area pertaining to Chemical Engineering and related Engineering and Science disciplines. The Department has state-of-the-art experimental and computational facilities and is the home of the Automated high-throughput platform suite, the Sargent Centre for Process Systems Engineering and the Sustainable Futures Lab.
The Department holds a Silver Athena Swan award for good practice in supporting academic women and gender equality renewed in 2024. This award recognises the good practices already in place for supporting women at all stages as well as our commitment to removing barriers to equal progress and achievement.
Deadline:
- 31 October 2026 for the first selection round
- 31 December 2026 for the second selection round
- 28 February 2027 for the third selection round (subject to availability of scholarships)
In order to be considered for the Chemical Engineering PhD Scholarships, you will need to submit your PhD application for admission through the online admissions system. Full details on the application and selection process can be found on our webpages.
We encourage all interested applicants to contact Dr Pietro Sormanni at pietro.sormanni@imperial.ac.uk before making an application.