University of Sheffield

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Research Associate (Bioinformatics, Population Genomics & Research Data Management) @ University of Sheffield

Sheffield, HybridHybridContract
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About this role

Job description:

We are seeking a Research Associate in Bioinformatics, Population Genomics & Research Data Management who is passionate about applying population genomics, data curation, and open science to address real-world ecological challenges.

In this role, you will play a central part in Technical Area 4 (TA4) of the ARIA Accelerated Adaptation programme. Working alongside Sheffield’s NEOF and Research Software Engineering (RSE) teams, as well as partners at the Earlham Institute, you will empower research groups across the UK to accelerate ecological adaptation through cutting-edge genomic and computational tools.

In this role you will use your expertise in bioinformatics, quantitative genetics, and data curation to co-develop reproducible bioinformatic pipelines and deliver hands-on data training to programme research teams. You will also perform independent re-analyses and verification workflows to ensure programme findings are robust, transparent, and rapidly accessible via interactive dashboards.

Applicants must hold a PhD (or be close to completion / have equivalent postdoctoral work experience) in Bioinformatics, Evolutionary Genomics, Quantitative Genetics, Computational Biology, or a relevant area along with experience in bioinformatic or population genomic analyses, including processing high-throughput sequencing (NGS) datasets. Strong programming skills (e.g., Linux/Bash, R, Python) and experience using High-Performance Computing (HPC) clusters are also essential.

We build teams of people from different heritages and lifestyles from across the world, whose talent and contributions complement each other to greatest effect. We believe diversity in all its forms delivers greater impact through research, teaching and student experience.

Skills

Biological SciencesHigher EducationBiologyComputer ScienceAcademic or ResearchSoftware EngineeringComputer SciencesGeneticsAcademic

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