Machine Learning Researcher in Bioinformatics (Research Fellow)

We are looking for an ambitious and talented postdoctoral researcher to join the Zelezniak Lab at King’s College London. Our lab sits at the forefront of synthetic biology and AI, creating next-generation tools for DNA, protein, and genome engineering. We aim to unravel the logic of genome organisation and metabolic control - with the bold vision of building synthetic life. In this role, you will develop and apply deep learning methods to analyse single-cell modalities, focusing on gene regulation and the engineering of microbial and human cells. You will work with cutting-edge AI approaches to design cellular phenotypes and optimise biochemical reactions. We welcome applicants from backgrounds, including computational chemistry, bioinformatics, systems biology, physics and machine learning.

The project offers a unique opportunity to collaborate closely with experimental scientists and contribute to translational advances in synthetic biology and AI.

This is a full time role (35 hours per week), and you will be offered a fixed term contract until 1st September 2028 starting no sooner than 1st November 2025.

To be successful in this role, we are looking for candidates to have the following skills and experience:

• PhD in bioinformatics, computational biology, or a related discipline
• Extensive experience and expertise in applying/developing and training deep learning models on biological, chemical or related datasets
• Proficiency in Python for data science and machine learning
• Possess sufficient breadth or depth of specialist knowledge with deep learning architectures including generative models, particularly for sequence or structural data (e.g. transformers, graph neural networks, diffusion models)
• Proved experience in working independently and as part of a multidisciplinary team
• Evidence of strong communication and scientific writing skills
• Evidence of publication track record
• Extensive experience and expertise in version control (e.g., Git) and reproducible research practices
• Experience working with generative models or large language models
• Experience with large scale GPU-based model training and cloud computing
• Knowledge of synthetic biology or regulatory sequence design
• Previous collaboration with experimental biologists or interdisciplinary teams

This range is provided by King’s College London. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

• Associate

• Full-time

• Research

• Higher Education