Postdoc: Biological Foundation Models Research Scientist

The Earlham Institute; Norwich; On-site; GBP 39,000 - 52,560; Full time

Job summary

The Earlham Institute in Norwich seeks a (Senior) Postdoctoral Research Scientist to develop biological foundation models within its AI for Biology Group. You will advance pretraining, post-training, adaptation and evaluation of multimodal models spanning DNA, RNA, genomics and imaging in a highly collaborative environment.

The role offers exposure to large‑scale AI compute and cross‑institution partnerships, shaping the Generative Digital Biology program and contributing to premier AI, ML and

Qualifications

• PhD in Computer Science, Machine Learning, AI, Computational Biology, Mathematics, Statistics, Physics, Engineering or related quantitative field (within 6 months)
• Excellent programming skills in Python; experience with PyTorch, JAX or TensorFlow
• Experience with large‑scale model training; GPU/HPC/cloud computing; reproducible research workflows
• Familiarity with biological data types (DNA/RNA, genomics, transcriptomics) and data governance

Responsibilities

• Develop original multimodal foundation model architectures for biological data across modalities.
• Lead a defined foundation-model workstream at SC5; set priorities, milestones and manage risks.
• Collaborate with internal EI teams to define AI-ready data atlases and benchmarks.
• Build representations connecting molecular to organismal scales for biology discovery.
• Translate model outputs into testable hypotheses or designs.
• Prepare research outputs for high‑level venues and grant applications.

Skills

Python

PyTorch

JAX

TensorFlow

HuggingFace

Education

PhD in CS/ML/Computational Biology

Tools

HuggingFace

DeepSpeed

FSDP

Megatron-LM

Ray

Job description

The Earlham Institute in Norwich seeks a (Senior) Postdoctoral Research Scientist to develop biological foundation models within its AI for Biology Group. You will advance pretraining, post-training, adaptation and evaluation of multimodal models spanning DNA, RNA, genomics and imaging in a highly collaborative environment.

The role offers exposure to large‑scale AI compute and cross‑institution partnerships, shaping the Generative Digital Biology program and contributing to premier AI, ML and