AI-Driven Plant Genomics Research Assistant

UAG; Cambridge; Remote; GBP 27,000 - 36,000; Full time

Benefits offered by this job

Family-friendly benefits

Development opportunities

Collaborative environment

Job summary

The Sainsbury Laboratory Cambridge University (SLCU) invites applications for a Research Assistant in the Yu Group. The role focuses on computational analysis of plant genomic and multi-omic data, with emphasis on developing and interpreting AI foundation models and collaborating with experimentalists.

The postholder will contribute to ongoing projects, process data on HPC systems, and assist in preparing manuscripts and funding applications.

Qualifications

• A first or Master’s degree in bioinformatics, computational biology, plant biology, molecular biology or a related field.
• Practical experience of bioinformatics analysis and programming in Bash, Python and/or R is essential.
• Foundation in machine learning and understanding of plant molecular biology and gene regulation.
• Practical wet-lab experience is desirable but not required; experience with statistics, HPC or deep learning frameworks is helpful.
• Good organisational skills, high accuracy and clear, reproducible record-keeping are essential.

Responsibilities

• Process and analyse genomic and multi-omic datasets on HPC systems using Bash, Python and/or R.
• Fine-tune and interpret AI foundation models and curate training datasets.
• Collaborate with experimental groups to analyse data and design predictive experiments.
• Perform statistical analyses and maintain reproducible code and results.
• Prepare figures, present results to the group and contribute to manuscripts and funding applications.

Skills

Bash

Python

R

Bioinformatics analysis

HPC experience

Education

Bachelor's or Master's in bioinformatics or related field

Tools

HPC systems

Git

Jupyter

Job description

The Sainsbury Laboratory Cambridge University (SLCU) invites applications for a Research Assistant in the Yu Group. The role focuses on computational analysis of plant genomic and multi-omic data, with emphasis on developing and interpreting AI foundation models and collaborating with experimentalists.

The postholder will contribute to ongoing projects, process data on HPC systems, and assist in preparing manuscripts and funding applications.