Research Associate - Locke Group (Fixed Term)

University of Cambridge; Cambridge; On-site; GBP 34,000 - 48,000; Full time

Job summary

The University of Cambridge invites applications for a Research Associate to join Professor James Locke's group at the Sainsbury Laboratory. The post will develop and apply machine-learning approaches, including DNA foundation models, to study how regulatory DNA sequences influence gene expression dynamics and cell-to-cell variability.

You will build and evaluate computational models linking promoters and regulatory elements to expression, test predictions with quantitative data, and work

Qualifications

• Strong programming skills in Python and/or R.
• Experience applying machine-learning methods to biological data.
• Good understanding of statistical analysis and model evaluation.

Responsibilities

• Develop, adapt and evaluate computational models linking regulatory sequences to gene expression.
• Test models using gene expression measurements and sequencing data.
• Collaborate with experimental researchers to guide tests of regulatory hypotheses.

Skills

Python

R

Machine learning

Statistics

Job description

Applications are invited for a Research Associate to join Professor James Locke's group at the Sainsbury Laboratory, University of Cambridge. The post will develop and apply machine-learning approaches, including DNA foundation models, to investigate how regulatory DNA sequences influence gene expression dynamics, variability between individual cells and plants, and responses to the environment.

The research

The successful candidate will develop, adapt and evaluate computational models that link promoters and other regulatory sequences to gene expression behaviour. Research questions include which sequence features influence expression variability, whether models can predict the effects of regulatory sequence changes, and how these relationships depend on environmental conditions and circadian timing.

A central focus will be exploring how DNA foundation models and other sequence-based approaches can help address these questions. The project offers scope to develop new methods, compare modelling approaches and identify regulatory features that generate testable biological predictions.

Models will be developed and tested using quantitative gene expression measurements, including fluorescent reporters, time-resolved transcriptomics and single-nucleus RNA sequencing. The post holder will work closely with experimental researchers to connect model predictions with measurements of gene expression and guide experiments that test how regulatory sequences shape expression variability and environmental responses.

The successful candidate will help shape the project's scientific and computational direction, building on their expertise and interests within these research aims.

Person specification

• strong programming skills in Python and/or R;
• experience developing or applying machine-learning methods to biological sequence, gene expression or related datasets;
• a good understanding of statistical analysis and model evaluation.

Experience with DNA foundation models, biological sequence modelling, deep learning, regulatory genomics or interpretable predictive modelling would be particularly valuable. Familiarity with plant biology, gene expression variability, circadian biology, transcriptomics or time-series analysis would also be advantageous.

Candidates should be self-motivated, able to work independently, and enthusiastic about close collaboration with experimental researchers.

Research environment and career development

The Locke group works across quantitative plant biology, gene regulatory dynamics and systems biology. The Sainsbury Laboratory offers an interdisciplinary research environment, mentoring and professional development opportunities.

The post holder will be supported in presenting and publishing research and, where appropriate, preparing applications for independent fellowships. Flexible working arrangements may be considered subject to the requirements of the role and University and Laboratory approval.

Fixed-term: The funds for this post are available for 16 months in the first instance.

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.