Postdoctoral Fellow - Evolution and Generative AI - Osipova Lab

Location: Greater London

Postdoctoral Fellow
- Evolution and Generative AI
- Osipova Lab Skip to main content# Careers at The Francis Crick Institute Postdoctoral Fellow
- Evolution and Generative AI
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- Evolution and Generative AI
- Osipova Lab Apply locations:
London time type:
Full time posted on:
Posted Todayjob requisition :
R2836
** Salary for this Role:
** From £47,500 with benefits, subject to skills and experience
*
* Job Title:

** Postdoctoral Fellow
- Evolution and Generative AI
- Osipova Lab
*
* Reports to:

** Ekaterina Osipova [C]
** Closing Date:
** 16/Aug/ GMT
*
* Job Description:

**** Postdoctoral Fellow - Evolution and Generative AI
**** Details of the role:
**** Reporting to:
** Katya Osipova - Group Leader
** Working pattern**:
This is a full-time, fixed term (4 years) position on Crick terms and conditions of employment.
** About us
** The Francis Crick Institute is Europe’s largest biomedical research institute under one roof. Our world-class scientists and staff collaborate on vital research to help prevent, diagnose and treat illnesses such as cancer, heart disease, infectious diseases and neurodegenerative conditions.

The Crick is a place for collaboration, innovation and exploration across many disciplines. A space where the brightest minds can pursue big and bold ideas and discover answers to crucial scientific questions. We support them in a dynamic environment which fosters excellence with state-of-the-art infrastructure, cutting-edge facilities, and a creative and curious culture. We’ve removed traditional boundaries of departments, divisions and disciplines and instead have an open approach that supports every researcher.

This gives us the freedom to take risks and carry out high-quality, pioneering research. Creating a space for discovery without boundaries helps us to turn our science into benefits for human health and the economy.
** About the Osipova lab
** The Osipova lab a new research lab opening at The Francis Crick Institute. We are focused on understanding how animals evolve a broad diversity of metabolic adaptations and how these biological innovations can be harnessed to engineer the next generation of metabolic systems.

To achieve this, we are developing two complementary research programmes:
* Comparative genomics and high-throughput functional screening to identify genotype–phenotype relationships and reveal the molecular basis of metabolic innovation.
* Generative AI-driven metabolic design, supported by experimental validation, to predict, create, and expand metabolic capabilities beyond those currently found in nature.

Together, these approaches aim to build a generalisable framework that translates evolutionary insights into synthetic biology and redefines the limits of metabolism.

Find out more about Osipova lab here
** About the role
** We are looking for a highly motivated postdoc with proven research abilities and an excellent publication record who will lead the development of the generative AI-based framework.

Specifically in this project, we will explore the potential of generative artificial intelligence to aid the design of novel metabolic systems. You will be working closely with the experimentalist in the lab to build ‘design-build-test-learn’ pipeline through computational design and experimental validation.
** What you will be doing
** You will:
* Develop, apply, and iteratively refine protein/genomic language models to design novel protein variants informed by evolutionary and phenotypic data
* Build computational pipelines linking sequence variation to predicted metabolic function
* Establish a design-build-test-learn cycle in close collaboration with the experimentalist in the lab, who will test designed variants
* Contribute to publications, conference presentations, and give strategic input into the wider direction of the lab's computational endeavours

Please see full job description here
** About you
*
* You will have:

* PhD (or in the final stages of PhD submission) in computational biology, evolutionary genomics, computer science, or a related field
* Strong analytical, quantitative, and coding skills (particularly in Python)
* Experience handling and…