Research Associate; Bioinformatics, Population Genomics & Research Data Management

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This post will involve providing core data and analytics support to the ARIA Accelerated Adaptation programme, delivered jointly by the University of Sheffield (NEOF, based in the Genomics Laboratory of the Ecology and Evolutionary Biology cluster in the School of Biosciences, & Research Software Engineering) and the Earlham Institute (COPO Project). The appointee will play a pivotal role in establishing a comprehensive data support framework for research teams across the programme.

Key responsibilities include co-developing and delivering training and bioinformatics support in data management, data deposition, and advanced bioinformatic workflows.

You will assist partner research groups with experimental design, study curation, and data analysis—likely to include low-coverage whole-genome sequencing, genotype imputation, genome-wide association studies (GWAS), genomic prediction, selection tests, and multi-omics.

In addition to providing training and bioinformatic support, the appointee will play a pivotal role in establishing shared bioinformatic pipelines (e.g., via Git Hub) and collaborating with RSE specialists to support independent verification of research findings by building re‑analysis workflows, evaluating scientific claims submitted by programme research groups, and helping populate shared results 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.

• Liaise with project leads and coordinate directly with research teams across the ARIA Accelerated Adaptation programme to identify analytical, data management, and training needs.
• Co‑develop and deliver tailored training workshops covering FAIR data principles, reproducible research data management, sample tracking, software best practices, and data deposition to public repositories (e.g., NCBI SRA).
• Establish, optimise, and disseminate reproducible bioinformatic pipelines and protocols (e.g., via shared Git Hub repositories) for population genomics, low‑coverage whole‑genome sequencing, genotype imputation, GWAS, genomic prediction, and multi‑omics analyses.
• Provide 1:1 analytical and bioinformatic support and guidance to partner research groups analysing complex genomic, transcriptomic, or phenotypic datasets.
• Collaborate with the Research Software Engineering (RSE) team to support the curation, independent verification, and presentation of findings through web‑based interactive data visualisations and dashboards.
• Build and execute verification pipelines to perform independent re‑analyses of analytical claims submitted by programme research teams.
• Set up and maintain Slack channels, version‑controlled code repositories, and documentation to facilitate informal support and cross‑project collaboration.
• Assist with the administration and execution of bioinformatic workflows on the University’s High‑Performance Computing (HPC) facility.
• Represent the project at meetings, workshops, and conferences as required.
• Continuously check project progress and adapt work schedules flexibly to accommodate new developments across supported research streams.
• As a member of staff, make ethical decisions in…