Postdoctoral Fellow in Computational Biology – Fröhlich lab

The Francis Crick Institute
Dynamics of Living Systems Laboratory
United Kingdom London London


Several research directions are being pursued and the successful candidate will have the freedom to develop and undertake their own independent research projects within the scope of the lab’s interests. Topics include development of hybrid models that use machine learning to contextualize ordinary differential equation (ODE) models from (single-cell) omics and imaging data; and the development of neural-network-based coarse-graining of protein-structure-based models. Application of these models include drug sensitivity prediction, protein design and cellular reprogramming.

The post holder will be responsible for:
- Leading and developing specific research projects
- Developing and maintaining computational tools
- Applying methods to biological data and interpreting results
- Collaborating with national and international partners
- Presenting work at lab meetings as well as national and international meetings
- Publishing scientific results
- Assisting in training graduate students and other members of the laboratory


- PhD in a relevant field or in the final stages of PhD submission
- Good knowledge and experience in coding (Python/Julia/C or similar languages)
- Technical expertise in mathematical modelling and/or machine learning
- An interest in applying computational methods to biological problems
- A demonstrated ability to generate and pursue independent research ideas
- Excellent communication skills, written and verbal as evidenced by publications, preprints and/or conference presentations
- Cross-disciplinary mindset, collaborative attitude, and teamwork experience
- Dedication to reproducible research and open science
- A cover letter that is tailored to the lab and the position

- Foundational knowledge in Cell Biology, Biochemistry and/or Systems Biology
- Foundational knowledge in Mathematics, Physics, Statistics and/or Data Science
- Background in numerical methods for optimization and solving differential equation models
- Familiarity with modern software development practices and high-performance computing
- Good command of a machine learning framework (jax/pytorch or similar)
- Experience working in interdisciplinary environments

Start date

To be determined

How to Apply



Fabian Fröhlich