Research Associate / Senior Research Associate in Biomolecular Statistical Analysis

The role

Join leading international researchers in the Organic Geochemistry Unit (University of Bristol) and the Molecular and Cultural Evolution Lab (UCL) on the NERC‑funded AquaNeo project, investigating the role and importance of aquatic resources in Prehistory. You will help test specific hypotheses using a formal model comparison framework applied to biomolecular datasets from Neolithic pottery.

Working pattern: This role offers hybrid working, with an expectation of 2 days per week on site and up to 3 days working from home, subject to operational needs, with regular visits to UCL.

Flexible working: We are happy to consider part-time applications (minimum 0.8 FTE).

Please note that this is an open-ended position with fixed funding until March 2027.

What will you be doing?

• Independently develop, implement, and validate statistical analyses of complex biomolecular data using R or Python, and draw defensible scientific inferences.
• Estimate dietary components and evaluate subsistence strategies using model comparison and quantitative statistical methods.
• Collaborate across Bristol and UCL teams; present analytical results and contribute to high‑quality, peer‑reviewed publications.

You should apply if

Essential:

• Degree or equivalent professional experience in Data Science, Statistics, Bioinformatics, Chemistry, Biology or Archaeology.
• Demonstrable, hands‑on proficiency in R or Python for statistical analysis of large, complex datasets, evidenced through research projects, publications, or reproducible analytical workflows.
• Ability to write and publish scientific manuscripts, data reports and analytical summaries.
• Excellent collaboration and communication skills; experience working with external partners or interdisciplinary teams.

Desirable

• Experience of archaeological research; understanding of isotopic and biomarker chemical data.
• Creative track record developing novel statistical/analytical approaches; experience working with external partners.

Qualifications

• Grade I: PhD awarded or near completion in a relevant field (e.g., Data Science, Statistics, Bioinformatics, Chemistry, Biology, Archaeology) or equivalent professional experience/qualification.
• Grade J: Relevant postgraduate research degree or equivalent professional experience in the required research area, with evidence of independent research and peer-reviewed publications.

This role would particularly suit a researcher with strong quantitative and statistical modelling skills who is interested in applying formal model‑comparison approaches to archaeological and biomolecular data. We welcome applications from candidates with backgrounds in data science, statistics, bioinformatics, chemistry, biology, archaeology, or related quantitative disciplines.

The role will be appointed at Grade I or Grade J, depending on skills, experience and qualifications.

For a full view of the requirements and responsibilities for this role, please refer to the attached job description.

Why join us?

Work at the interface of chemistry, data science and archaeology to produce new insights into prehistoric diets and subsistence strategies, within a supportive, collaborative environment spanning Bristol and UCL.

Additional information

Contract type: Open ended (funding available until 31.03.2027)

The position is funded for a fixed term of 17 months. Further funding may become available to extend this employment.

Work pattern: Full-time or part-time hours considered

This advert will close at 23:59 UK time on 16/02/2026

For informal queries, please contact: Dr Melanie Roffet-Salque, melanie.salque@bristol.ac.ukProf Mark Thomas, m.thomas@ucl.ac.uk

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