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/.
Please ensure that you upload a copy of your full CV, and a cover letter highlighting your suitability for the position and contact information of three referees.
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.
Click the 'Apply' button below to register an account with our recruitment system (if you have not already) and apply online.
Scientific enquiries apart from the formal application should be directed to Dr Haopeng Yu at [email protected] (https://www.slcu.cam.ac.uk/people/haopeng-yu).
For questions regarding the application process, please email [email protected]
Please quote reference PT51536 on your application and in any correspondence about this vacancy.
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.