Research Associate in Machine Learning for Protein Design

About the role

Are you interested in applying protein design tools to real-world problems? You will work on engineering proteins for optimised expression and nutrition. You will design and engineer proteins and then characterise them.

What you would be doing

You will design, engineer, and characterise proteins with improved nutritional performance and expression, using a combination of machine-learning-assisted protein design tools and experimental validation. This will include applying and extending deep-learning approaches such as RFDiffusion and ProteinMPNN, developing in-house computational workflows, and carrying out expression, purification, and biochemical characterisation to ensure robust, reproducible results suitable for publication and downstream application. You will contribute to the scientific direction of the project, plan and prioritise your own research activities, and maintain accurate experimental records and data analysis throughout.

You will work collaboratively within the National Alternative Protein Innovation Centre (NAPIC) network at Imperial and with external partners, contributing to high-quality publications, conference presentations, and research reports. The role also involves supporting the supervision of students, contributing to grant proposals and collaborative projects, and helping to strengthen the wider research environment through engagement in group meetings, knowledge exchange, and interdisciplinary collaboration focused on advancing sustainable alternative protein technologies.

What we are looking for

We are looking for a motivated and collaborative researcher who brings a strong technical foundation in proteins alongside curiosity and initiative. In particular, you will have:

• Experience with proteins and protein structure machine learning tools such as RFDiffusion and ProteinMPNN.
• Skills in data analysis or using machine learning tools.
• The ability to work independently and collaboratively within an interdisciplinary and international research team
• Strong written and verbal communication skills, with experience contributing to academic publications or technical reports
• A proactive, organised approach to research, with the ability to manage competing priorities and meet deadlines
• An open, flexible mindset and enthusiasm for interdisciplinary, impact-oriented research.

What we can offer you

• The opportunity to work on an important research problem at the intersection of machine learning, protein design, and food security.
• Support to develop an independent research profile, including opportunities to publish in high-impact journals, contribute to grant applications, and present at international conferences
• Access to excellent computational resources, training, and professional development offered by Imperial College London
• Opportunities to supervise and mentor PhD students, MSc projects, and early career researchers
• A supportive and inclusive working environment that values open science, responsible AI, and real-world impact
• The opportunity to continue your career at a world-leading institution and be part of our mission to continue science for humanity.
• Grow your career: gain access to Imperial’s sector-leading dedicated career support for researchers as well as opportunities for promotion and progression.
• Sector-leading salary and remuneration package (including 41 days off a year and generous pension schemes).
• Be part of a diverse, inclusive and collaborative work culture with various staff networks and resources to support your personal and professional wellbeing.

Further information

This post is full time, fixed term for up to 30 months.

Candidates who have not yet been officially awarded their PhD will be appointed as Research Assistant.

The expected start date is as soon as possible.

If you require any further details about the role, please contact: Dr James Murray – j.w.murray@imperial.ac.uk

Available documents