Location: | Cambridge |
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Salary: | £32,546 to £35,116 per annum |
Hours: | Full Time |
Contract Type: | Fixed-Term/Contract |
Placed On: | 18th June 2025 |
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Closes: | 16th July 2025 |
Job Ref: | RE46358 |
The Mitchell Group at the Cambridge Early Cancer Institute is seeking a highly motivated and skilled Research Assistant with a background in computational biology to join their team specialising in kidney cancer research. This is an exciting opportunity to contribute to a large-scale, collaborative project investigating the genomic evolution of kidney cancer, using a uniquely rich cohort of patient samples and data. The project integrates whole-genome sequencing, transcriptomics, epigenetic profiling, and clinical information to uncover the key molecular drivers that underpin tumour progression and therapeutic response.
The successful candidate will play a central role in the group's research efforts, taking responsibility for the curation, analysis, and integration of complex, large-scale genomic datasets. This includes the processing and quality control of whole-genome sequencing data, methylation data, and RNA-sequencing data, as well as the development and application of computational methods to derive meaningful biological insights. The role also involves generating clear and informative data visualisations and contributing to discussions and decision-making within the wider research team. The ability to maintain well-documented, reproducible analysis pipelines is essential, as is a commitment to open, collaborative science.
Applicants should hold a Master's degree or equivalent in Computational Biology, Bioinformatics, Genomics, Data Science, Biostatistics, or a related field. They should have experience analysing high-throughput sequencing data, particularly whole-genome sequencing, methylation, and/or RNA-seq. Proficiency in programming languages commonly used in genomics, such as Python and/or R, along with familiarity with Bash scripting, is essential. The ideal candidate will demonstrate not only strong technical skills but also a genuine enthusiasm for applying computational approaches to pressing questions in cancer biology. Prior experience in multi-omics data integration is highly desirable. This role offers opportunities for professional development, including access to specialised training in cancer genomics and bioinformatics.
Please review the Further Particulars in full before submitting an application.
Please ensure that you upload a covering letter and 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 closing date for applications is 16 July 2025
Fixed-term: The funds for this post are available for 2 years in the first instance.
Once an offer of employment has been accepted, the successful candidate will be required to undergo a health assessment.
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 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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