The Generative Biology Institute commenced operations in 2025, occupying newly renovated bespoke space in the Oxford Science Park. The team will later move to a purpose-made facility in the Oxford Science Park, currently under construction. Once complete, this state-of-the-art facility will include more than 40,000 m² of research laboratory and office space. It will house over 30 groups and up to 600 employees at scale, focused on solving the two critical challenges in making biology engineerable and applying the solutions to addressing the global challenges encapsulated in EIT's Humane Endeavors.

Your Role:

At EIT, we are seeking an experienced and detail-oriented Bio-ML Scientist (Senior & Non-Senior) to develop AI and machine learning systems that drive and catalyse GBI's scientific aims, working alongside researchers and platform staff to address key questions in biological sequence design and discovery. The post-holder will work with multiple data modalities with a focus on sequence-to-function modelling, prediction, and optimisation.

This is an exceptional opportunity to join a new unit at the forefront of AI/ML and synthetic biology with access to exceptional facilities and expertise. We are looking for colleagues who thrive in a team and care deeply about biological questions, hypotheses, and a biology-centric approach to AI/ML engineering. The role requires broad technical expertise in applied machine learning and prior exposure to synthetic biology design tasks in collaboration with wet lab scientists. Our team ethos is based on mutual learning, strong peer-to-peer support, and a deep sense of scientific curiosity and ambition. We are hiring at regular or senior level depending on experience.

Key Responsibilities:

• Design and build AI and machine learning systems to address GBI's research challenges in synthetic biology, genome design, and molecular evolution
• Lead and contribute to collaborative projects with GBI researchers, staff, and external collaborators
• Work closely with GBI wet lab scientists in co-creation of research projects and development of fit-for-purpose computational solutions
• Provide expert machine learning know-how to GBI researchers and scope novel avenues of research
• Interact with the Bioinformatics and Scientific Compute platform teams to support the development of GBI data flows and MLOps
• Ensure compliance with best practices in ML engineering, including robust and reproducible training pipelines, as well as versioning and documentation of data, models, and code
• Keep abreast of progress in AIxBio and make use of strategic learning opportunities
• Lead and contribute to research publications in prestigious venues
• Organise and prioritise work, operating at the highest standard in the face of multiple competing deadlines
• Promote and champion EIT and the work of the GBI, representing the institute at functions and public events

Requirements

Essential Knowledge, Skills, and Experience:

• PhD degree in a suitable field including, but not limited to, mathematics, computer science, molecular biology, computational biology, engineering, or related discipline. Desirable: at least 2 years of industry or postdoctoral in similar roles
• Experience in building AI or machine learning models for biological design tasks, involving processing, visualizing, and analysing various data modalities in collaboration with wet lab scientists and using a breadth of methods and architectures (such as classic statistical learning, genomic/protein foundation models, deep learning, genome-scale metabolic models, representation learning, multi-modal learning, active learning).
• Ability to abstract high-level biological questions and translate them into actionable machine learning tasks, evidenced by previous achievements in a comparable industry role, or a promising publication record in scientific journals and technical conferences.
• Ability to learn quickly and dive into a range of problem spaces and computational methods.
• Ability to work and communicate with and within diverse and multidisciplinary teams.
• Fluency in one or more scientific programming languages (Python, R, Julia, etc) with experience in best practices in machine learning, including documentation.
• Excellent written and oral communication skills for diverse audiences, including colleagues without a computational background.
• Excellent time management skills across competing tasks requiring rapid context switching.

Benefits

Our Benefits:

• Competitive Salary + travel allowance + bonus
• Enhanced holiday pay
• Pension
• Life Assurance
• Income Protection
• Private Medical Insurance
• Hospital Cash Plan
• Therapy Services
• Perk Box
• Electric Car Scheme

Working Together - What It Involves:

• You must have the right to work permanently in the UK with a willingness to travel as necessary. In certain cases, we can consider sponsorship, and this will be assessed on a case-by-case basis
• You will live in, or within easy commuting distance of, Oxford (or be willing to relocate)