PhD Scholarship: AI for Antibody and Protein Design (2026/27)

PhD Scholarship: AI for Antibody and Protein Design (2026/27)

Institution: Imperial College London Department: Department of Chemical Engineering Research Group: Sormanni Group (prediction and design of protein developability) Topic: AI for Antibody and Protein Design Funding Type: Fully Funded Studentship Location: London, United Kingdom

Scholarship Overview

Imperial College London, consistently ranked among the top ten universities in the world, is inviting applications for a prestigious, fully funded PhD studentship starting in the 2026/2027 academic cycle.

This PhD project is situated within the Department of Chemical Engineering, a world-leading hub for engineering and scientific research. The project focuses on one of the most transformative areas of modern science: the intersection of Artificial Intelligence (AI) and Biotechnology.

The successful candidate will work on developing innovative AI methods to design therapeutic-grade antibody and protein sequences. This is a unique opportunity to contribute to research that has the potential to revolutionize drug discovery and medicine, working at the forefront of the “AI for Science” wave.

Research Context: Why This Matters

The field of protein design is currently undergoing a paradigm shift driven by machine learning. Antibodies and proteins are the workhorses of modern medicine, used to treat everything from cancer to autoimmune diseases. However, designing these molecules to be safe, effective, and stable (manufacturable) is a notoriously difficult and expensive challenge.

The Project Mission: This PhD will focus on developing computational tools that can predict and optimize the properties of proteins. By leveraging Generative AI and Machine Learning (ML), the project aims to:

• Accelerate the discovery of new therapeutic antibodies.

• Design protein sequences that are not only biologically active but also “developable” (stable and soluble).

• Bridge the gap between computational predictions and real-world laboratory experiments.

Funding and Benefits

This is a Fully Funded Studentship. While specific values change annually, a fully funded PhD at Imperial College London typically includes:

• Full Tuition Fees: Coverage of the full cost of tuition for the duration of the program.

• Living Stipend: A tax-free maintenance grant (stipend) to cover living costs in London.

• Research Costs: Access to high-performance computing (HPC) resources, conferences, and consumables required for the research.

• Professional Development: Access to Imperial’s Graduate School, offering comprehensive training in transferable skills, research methodology, and career planning.

Eligibility and Candidate Profile

We are looking for a highly motivated individual who is eager to work at the interface of computation and biology. You do not need to be an expert in biology to apply, but you must have a passion for solving complex biological problems using quantitative methods.

Essential Requirements:

• Academic Background: A strong undergraduate or master’s degree in a quantitative discipline (e.g., Chemical Engineering, Computer Science, Physics, Mathematics, or Bioengineering).

• Technical Skills: A strong interest and proficiency in coding, particularly in Python.

• Quantitative Mindset: Strong analytical and quantitative thinking skills are essential for modeling complex systems.

• Motivation: A clear motivation to apply machine learning skills to the field of protein and antibody design.

Desirable (But Not Essential) Skills:

• Prior experience in Machine Learning (ML) or Deep Learning.

• Familiarity with biological concepts or bioinformatics.

Note: The department values potential and the ability to learn quickly. If you have strong coding skills and a math/physics background, do not be deterred by a lack of biology experience.

Why Choose Imperial College London?

1. World-Class Reputation: Study at an institution renowned globally for its impact on science, engineering, and medicine.

2. Strategic Location: Based in South Kensington, London, you will be at the heart of a global scientific and cultural capital.

3. Collaborative Environment: The Sormanni Group and the wider Department of Chemical Engineering offer a vibrant, interdisciplinary environment where you will collaborate with experts ranging from software engineers to wet-lab experimentalists.

4. Career Prospects: Graduates from Imperial’s PhD programs are highly sought after by top-tier pharmaceutical companies, biotech startups, and leading academic institutions worldwide.

Application Process

Application Deadline: Open / Not Specified (Early application is strongly advised).

As this is a specific research group studentship, the application process often starts with an informal inquiry before the formal university application.

Step 1: Informal Inquiry Interested candidates are strongly encouraged to contact the Principal Investigator directly to discuss the project and their suitability.

Who to Contact: Please email Dr. Pietro Sormanni at: Email: pietro.sormanni@imperial.ac.uk

What to Include in Your Email: To make a professional impression, your email should be concise and include:

1. Subject Line: “PhD Inquiry: AI for Antibody Design – [Your Name]”

2. CV/Resume: A detailed CV highlighting your academic grades, coding experience (Python), and any research projects.

3. Cover Letter/Statement: A brief explanation (2-3 paragraphs) of why you are interested in this specific project and how your skills (e.g., coding, quantitative analysis) fit the requirements.

Step 2: Formal Application Following a successful discussion, you will be guided on how to submit a formal application through the Imperial College London admissions portal.

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