Senior Bioinformatician

Join us at the world-leading CRUK Cambridge Institute. We're a unique department of the University of Cambridge, core funded by Cancer Research UK's charitable activities, and we're eagerly searching for a Senior Bioinformatician to join the Mair Group and lead computational analysis of metabolic heterogeneity in glioblastoma. The project will build on established and newly generated datasets to understand how tumour metabolism varies between and within patients, how metabolic state shapes tumour phenotype and heterogeneity, and how these processes influence response to therapy.

A central focus will be the development and application of metabolic flux analysis paradigms, integrating isotope-tracing and mass-spectrometry-derived measurements with genomic, transcriptomic, epigenomic, single-cell, spatial and phenotypic data. The post-holder will use these data to identify metabolic programmes associated with distinct tumour states and therapeutic vulnerabilities, and to determine how metabolism changes during tumour evolution and treatment.

This Grade 8 role will provide senior computational leadership for the programme. The post-holder will develop robust and reproducible analytical frameworks for metabolic and multi-omic data, integrate deeply characterised metabolic datasets with larger existing cohorts, and explore machine-learning and deep-learning approaches that can infer metabolic state, explain biological heterogeneity and predict treatment response. The role offers considerable scope to develop new computational methodology at the interface of cancer metabolism, systems biology and data science.

Key responsibilities

Working with Dr Mair, experimental cancer metabolism researchers, computational collaborators and clinical scientists, your key responsibilities will be to:

• Lead the design, implementation and validation of reproducible computational pipelines for metabolic profiling, isotope-tracing and metabolic flux analysis in glioblastoma.
• Develop quantitative approaches to link metabolic flux and metabolomic measurements to tumour phenotype, cellular state, intratumoural heterogeneity and response to therapy.
• Integrate metabolic datasets with genomics, transcriptomics, epigenomics, single-cell and spatial datasets, and where appropriate imaging, pathology and longitudinal clinical information.
• Apply statistical, machine-learning and deep-learning methods to identify metabolic programmes, infer metabolic state from larger datasets and develop predictive models of tumour behaviour and treatment response.
• Develop rigorous quality-control, normalisation, harmonisation and benchmarking frameworks across metabolic platforms, cohorts, experimental systems and timepoints.
• Work closely with experimental scientists to translate biological questions into computational analyses and to design experiments that maximise the interpretability of metabolic flux and multi-omic data.
• Lead computational analyses for high-quality publications, presentations and grant applications, and communicate complex quantitative concepts to multidisciplinary biological and clinical audiences.
• Provide day-to-day technical leadership and mentoring for junior computational researchers and students, and contribute to the longer-term development of the Mair Group computational metabolism programme.

Fixed-term: The funds for this post are available for 3 years in the first instance.

To apply online for this vacancy and to view further information about the role, please click the 'Apply' button above.

Please ensure that you upload a covering letter and a CV in the Upload section of the online application. The covering letter should outline how you match the criteria for the post and why you are applying for this role. If you upload any additional documents which have not been requested, we will not be able to consider these as part of your application.

Please include details of your referees, including email address and phone number, one of which must be your most recent line manager.

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

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