Postdoctoral Research Fellow (Chin Lab) - Generative Biology Institute

• Health, Medical Science & Generative Biology
• Food Security & Sustainable Agriculture
• Climate Change & Managing CO₂
• Artificial Intelligence & Robotics

This is ambitious work - work that demands curiosity, courage, and a relentless drive to make a difference. At EIT, you'll join a community built on excellence, innovation, tenacity, trust, and collaboration, where bold ideas become real-world breakthroughs. Together, we push boundaries, embrace complexity, and create solutions to scale ideas from lab to society.

Welcome to the Generative Biology Institute:

Led by Founding Director Jason Chin, the Generative Biology Institute (GBI) at the Ellison Institute of Technology is tackling the key challenges in making biology engineerable, and thereby releasing the unrivalled power of biology for the benefit of humanity.

The vision of GBI is to lay the foundations for engineering biology, and unlock its potential for good. To achieve this, we must overcome two key challenges. First, we need the ability to write in the natural language of biology, enabling the rapid and scalable synthesis of entire genomes with precision. Second, we must understand what to write - determining which DNA sequences will generate biological systems that perform the desired functions. Addressing these challenges will allow us to harness the full power of biology to create transformative solutions across health, agriculture, clean energy and more.

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 Endeavours.

The AI & Robotics Team

The AI & Robotics team at EIT brings together AI research, robotics and scientific expertise to make biological matter computable and testable, at scale, and by any scientist. We build generative and predictive models of biological molecules and systems, physics-grounded simulation and design tools, and autonomous laboratories that generate the data these models learn from and test the designs they propose.

Project Monera

You will be joining the project Monera, a joint project across the Generative Biology Institute and the AI & Robotics team building multi-modal generative models of whole organisms, starting with Escherichia coli in order to understand and predict an organism's phenotype from its genome and environment and, in time, to design genomes for a desired function. The team works as one integrated computational and experimental group: experimentalists generate genetic variation and quantitative measurements at scale (growth and fitness, transcriptomics, proteomics, metabolomics), the models are trained and validated on that data, and the results shape the next round of experiments and insights. The experimental work is based in GBI's laboratories in the Oxford Science Park, alongside GBI's automation capability and in daily contact with the AI scientists in the AI & Robotics team.

Job Summary

We are building a joint experimental computational team focussed on building, training and validating multi-modal biological models.

The team will: i) generate experimental perturbation and measurement data at scale, ii) build multi-modal biological models and, iii) use the experimental data they generate to train and validate the multi-modal biological models they build.

In this role you will: i) perform experimental genome engineering work to generate genetic variation at scale and/or ii) design and implement scalable biological measurement over one or more modalities. Where appropriate the work will leverage the substantial automation capability within the institute. Your work will be performed under the guidance of Jason Chin.

You will be part of a single team composed of AI scientists and synthetic biologists working together. We are looking for colleagues with deep expertise in genome engineering and/or quantitative phenotyping of model bacterial species such as Escherichia coli. The role requires the ability and willingness to work as part of a cross-disciplinary team at the interface of computational and wetlab biology. Our team ethos is based on mutual learning, strong peer-to-peer support, and a deep sense of scientific curiosity and ambition.

This is your opportunity to be part of cutting-edge research within an institute dedicated to engineering biology at an unprecedented scale. You will be leveraging GBI's exceptional facilities, sustained funding, and collaborative environment. You will design and execute experiments, contribute to high-impact publications, and play a key role in the training and mentorship of junior researchers and students. Working at the interface of biology, AI, technology, and engineering, you will help shape GBI's vision to reimagine what's possible in biology.

Key Responsibilities:

• Design, execute, and troubleshoot experiments, including the development of novel methodologies and adaptation of existing techniques to new applications. In particular, the successful applicant will utilise genome engineering strategies in the lab to produce a diversity of microbial strains as the source of training and validation data in a high throughput fashion. In addition, they will also design and prototype a range of experimental measurement strategies for characterising these strains at scale.
• Collaborate with other GBI scientists from other groups expert in synthetic biology, automation, bioinformatics, -omics and machine learning, and AI scientists from the AIR institute, as required.
• Analyse complex datasets using computational and statistical tools, interpreting results in the context of broader research goals.
• Contribute intellectually to the research direction by identifying opportunities for innovation and refining research questions.
• Prepare and publish high-quality scientific papers, reports, presentations, and protocols.
• Present research at national and international conferences, seminars, and internal meetings.
• Collaborate with multidisciplinary teams within GBI, EIT, and external partners to advance complementary workstreams.
• Build and maintain research infrastructure, laboratory capabilities, and cutting-edge technologies.
• Mentor and support junior researchers, including PhD students and research assistants.
• Translate research findings into commercial or translational opportunities in alignment with EIT's mission.
• Identify and pursue opportunities for intellectual property generation and protection.
• Ensure research activities comply with EIT's policies, legal requirements, and best scientific practice.

This list is not exhaustive and the role holder may be required to undertake additional tasks and duties commensurate with the role.

Requirements

Relevant, Skills and Experience:

• Completed a PhD in a relevant field (e.g., synthetic biology, computational biology and AI, microbial genomics, cell biology, genomics, robotics and automation, metabolomics, and proteomics.).
• Track record of delivering ambitious research projects to a high standard.
• Strong track record in research, ideally in molecular biology, synthetic biology, or related fields.
• Skilled in data analysis and interpretation; experience with genomic analysis, automation, or computational tools desirable.
• Proven ability to work independently, think creatively, and solve complex experimental problems.
• Experience publishing in high-impact journals and presenting at international conferences.
• Excellent organisational skills with the ability to manage multiple concurrent projects.
• Strong written and verbal communication skills, with experience collaborating in multidisciplinary teams.
• Capacity to build and sustain productive collaborations internally and externally.
• Resilience, adaptability, and enthusiasm for working in a fast-paced, high-growth research environment.
• Deep scientific curiosity and the drive to run ambitious experiments at scale, which can be used for the training and validating foundation models for the purpose of understanding and predicting an organism's phenotype from its genome and environment.
• Basic familiarity with machine-learning concepts is welcome (what a model needs from data: coverage of the variable space, controls, replication, consistent metadata).

Benefits

Our Benefits:

• Annual Bonus
• Travel Allowance
• Enhanced sick pay
• Pension - Employer contribution 7.5%, minimum employee contribution 5%
• Life Assurance
• Income Protection
• Private Medical Insurance as standard for you, your partner and any dependents. Including hospital Cash Plan
• Employee discounts
• Electric car scheme
• Nursery Salary Sacrifice scheme
• Cycle to Work Scheme
• Family Planning
• Neurodiversity support including advise and assessments
• Coaching & Therapy services

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).