Research Assistant - Yu Group (Fixed Term)

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

Applications are invited for a Research Assistant in the group of Dr Haopeng Yu at the Sainsbury Laboratory Cambridge University (SLCU).

The Yu Group develops AI methods to understand how plants use genetic information to build different cell types, regulate gene expression and respond to their environment. We build interpretable AI and biological foundation models that learn the regulatory "language" of plant genomes and RNA and use them to decode the function of non-coding sequences and to generate hypotheses for experimental testing. The group also develops AI agents as virtual research partners for plant scientists.

More information about the group and Dr Yu's research can be found at: https://www.slcu.cam.ac.uk/research/research-groups/yu-group and https://www.slcu.cam.ac.uk/people/haopeng-yu.

The post holder will contribute to the group's ongoing research projects, including processing and analysing plant genomic and multi-omic data on high-performance computing (HPC) systems, fine-tuning and interpreting AI foundation models, and helping prepare manuscripts and funding applications. This is a fully computational role, suited to candidates with a background or strong interest in bioinformatics and computational biology.

Main responsibilities will include:

• Processing and analysing genomic and multi-omic datasets on HPC systems, using bioinformatics tools and pipelines in Bash, Python and/or R
• Fine-tuning and interpreting AI foundation models, including preparing and curating training datasets
• Working with experimental collaborators to analyse and interpret their data, and to design predictions for experimental testing
• Carrying out statistical analysis and keeping clear, reproducible records of code and results
• Preparing figures, presenting results to the group, and contributing to manuscripts and funding applications

Candidates should hold 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, together with a foundation in machine learning and an understanding of plant molecular biology and gene regulation. Practical wet-lab experience, which helps in understanding and interpreting experimental data, would be desirable, as would experience with statistical analysis, HPC or deep learning frameworks. Good organisational skills, a high degree of accuracy including outstanding record keeping, and the ability to work both independently and as part of a team are essential.

The Laboratory provides a welcoming and collaborative environment with a wide range of family-friendly benefits and development opportunities. More about the Sainsbury Laboratory and details of what the University offers to employees can be found at: http://www.slcu.cam.ac.uk/.

The post is available with a start date as soon as possible.

Fixed-term: The funds for this post are available for 1 year in the first instance.

Scientific enquiries apart from the formal application should be directed to Dr Haopeng Yu at [e-mail] (https://www.slcu.cam.ac.uk/people/haopeng-yu).

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.

The University has a responsibility to ensure that all employees are eligible to live and work in the UK.