Postdoctoral Research Fellow; Chin Lab; Generative Biology Institute

EIT - Ellison Institute of Technology

Oxford, United Kingdom

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.

• 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 work streams.
• 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.

• 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).