Senior Postdoctoral

To be considered for the role of Senior Research Fellow, the candidate must:

Hold a PhD specialising in statistics, biostatistics, applied mathematics, computational biology, bioinformatics or a closely related quantitative discipline applied to biological or biomedical research. At least three years of relevant postdoctoral research experience. A strong publication track record appropriate to career stage demonstrating substantial intellectual contributions to quantitative/computational research, including first or co-first author publications. Evidence of scientific independence, including the ability to formulate research questions and independently design and lead quantitative investigations. Advanced expertise in statistical and/or computational modelling of complex biological systems, beyond routine application of established analysis pipelines. Experience contributing to experimental/study design, including consideration of statistical power, replication, confounding, batch effects and appropriate analytical strategies. Experience leading multidisciplinary projects and working closely with experimental scientists. Experience mentoring or supervising junior researchers and providing technical/scientific leadership. Evidence of rigorous and reproducible computational research practices, including version control, documented analytical workflows and appropriate statistical validation. Ability to contribute intellectually to manuscripts, grant applications and the development of new research directions.

2. About the role of Postdoctoral

The Research Fellow will work closely with the laboratory's Senior Research Fellows and experimental scientists to independently lead computational projects, formulate quantitative approaches to biological questions, contribute to experimental design, develop rigorous analytical strategies, and help prioritise computational findings for mechanistic investigation and experimental validation.

To be considered for the role of Research Fellow, the candidate must:

Hold a PhD in bioinformatics, computational biology, statistics, biostatistics, applied mathematics, quantitative biology, or a closely related discipline. Demonstrate a strong research track record appropriate to career stage, including first- or co-first author publications demonstrating substantial intellectual or quantitative contributions. Demonstrate the ability to independently design and conduct rigorous computational or statistical investigations. Demonstrate experience analysing complex biological datasets and taking projects from raw data through statistical analysis, biological interpretation and publication. Have strong foundations in statistics and quantitative reasoning, including an understanding of experimental design, confounding, multiple testing, uncertainty and appropriate model validation. Demonstrate experience developing, adapting or critically evaluating computational/statistical approaches beyond relying exclusively on established analysis pipelines. Demonstrate the ability to work closely with experimental scientists to translate biological questions into analytical strategies and computational findings into experimentally testable hypotheses.

3. About the role of Bioinformatician

The Research Assistant / Bioinformatician will work closely with the laboratory's computational and experimental scientists to analyse complex biological datasets, implement and develop reproducible analytical workflows, contribute to the interpretation of results, and help generate hypotheses for subsequent experimental investigation. The successful candidate will be encouraged to develop increasing scientific and analytical independence as their experience grows.

To be considered for the role of Research Assistant / Bioinformatician, the candidate must:

Hold a Bachelor's or Master's degree in bioinformatics, computational biology, statistics, biostatistics, applied mathematics, computer science, quantitative biology, or a closely related discipline. Candidates from other quantitative backgrounds with demonstrable relevant experience will also be considered. Demonstrate proficiency in at least one programming language used for data analysis, preferably R and/or Python. Demonstrate experience analysing complex datasets using rigorous and reproducible computational approaches. Have a sound understanding of fundamental statistical concepts and their application to biological data. Demonstrate the ability to work with large-scale biological datasets, ideally including sequencing, proteomics, imaging, or other high-dimensional data. Demonstrate careful analytical practice, including data quality assessment, appropriate statistical testing, documentation and interpretation of results. Be able to communicate analytical findings clearly to computational and experimental collaborators. Demonstrate an ability and willingness to learn new computational, statistical and biological methods as required by individual projects.