Postdoctoral Research Fellow - Generative Biology Institute

About the Generative Biology Institute

The Generative Biology Institute (GBI) is tackling the key challenges in making biology engineerable, thereby unlocking the unrivalled power of biology for the benefit of humanity. GBI is part of the Ellison Institute of Technology, Oxford (EIT) and is led by founding Director Jason Chin.

The vision of the Generative Biology Institute is to lay the foundations for engineering biology, and unlock its potential for good. To achieve this, we must overcome two key challenges: first, the ability to write in the natural language of biology, enabling the rapid and scalable synthesis of entire genomes with precision; second, a deep understanding of which DNA sequences will generate biological systems that perform the desired functions.

Addressing these challenges will enable transformative solutions across health, agriculture, clean energy and more.

GBI has sustained and substantial funding and access to cutting‑edge technology hubs, compute resources, and a collaborative environment that supports ambitious, long‑term research and translates discoveries into commercial applications where appropriate.

The institute will commence operations in a newly renovated bespoke space in the Oxford Science Park and later move to a purpose‑made facility under construction expected to include more than 40,000 m² of laboratory and office space for over 30 groups and up to 600 employees.

We are seeking ambitious, creative, and highly skilled Postdoctoral Researchers to join GBI. In this role you will design and execute experiments, contribute to high‑impact publications, and mentor junior researchers. Working at the interface of biology, technology, and engineering, you will help shape GBI’s vision to reimagine what’s possible in biology.

Applications will be reviewed on a rolling basis by the specific research groups you select. Please choose up to three research groups and, in your cover letter, identify each group and explain your fit, interest, and relevant experience. Applications to more than three groups or without specified groups will not be considered.

All applications must be submitted exclusively through the EIT job portal. Due to the volume of applications, the review and decision process may take 3‑6 months.

• Leopold Parts – The Parts group works to engineer and model mammalian chromosomes, with long‑term aims to delete, randomise, evolve, and model chromosome‑scale DNA.
• Sam Pellock – The Pellock group combines advances in protein design with wet‑lab experimentation to design new enzymes, explore new‑to‑nature chemistry, and better understand enzyme function.
• Linda van Bijsterveldt – The van Bijsterveldt group develops methods for building and stably transmitting synthetic chromosomes through mitosis and meiosis in mammals and plants, focusing on scalable platform construction, cross‑species chromosome transfer, and control of trait inheritance.
• Jérôme Zürcher – The Zürcher group develops methodology to rapidly write entire genomes of microbes and phages, enabling genetic isolation, host‑pathogen interaction studies, and large vector assembly for genome synthesis.
• Kiarash Jamali – The Jamali group integrates large databases and inductive biases into generative models of biomolecules, creating tools for protein design of novel enzymatic reactions, therapeutics, and molecular motors, with focus on ML force fields.
• Fabian Rehm – The Rehm group develops approaches for continuous evolution of target genes and synthesis of large microbial genome stretches, focusing on evolving complex traits, selective pressures, and principles of natural evolution.
• Martin Spinck – The Spinck group explores biological evolution in artificial environments to uncover new‑to‑nature functions, focusing on evolvable self‑assembling biomaterials for sustainable chemistry and biotechnology.
• Rongzhen Tian – The Tian group leverages an orthogonal replication system for accelerated evolution of complex functions, advancing scientific understanding, developing biomolecules for health and industry, and generating large enzyme datasets for protein design…