At a Glance
- Tasks: Analyse biomolecular data to uncover insights into prehistoric diets and subsistence strategies.
- Company: Join a leading research team at the University of Bristol and UCL.
- Benefits: Flexible hybrid working, competitive salary, and opportunities for professional growth.
- Other info: Open-ended position with funding until March 2027; part-time applications welcome.
- Why this job: Make a real impact in archaeology using cutting-edge statistical methods.
- Qualifications: Degree in Data Science, Statistics, Bioinformatics, Chemistry, Biology, or Archaeology required.
The predicted salary is between 36000 - 60000 € per year.
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:
- 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.
- 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.
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 March 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
- Grade: I/J/Pathway 2
- School/Unit: School of Chemistry
This advert will close at 23:59 UK time on 16/02/2026. The interviews are anticipated to take place early March 2026.
For informal queries, please contact: Dr Melanie Roffet‑Salque, Mark Thomas.
The University of Bristol aims to be a place where everyone feels able to be themselves and do their best in an inclusive working environment where all colleagues can thrive and reach their full potential. We want to attract, develop, and retain individuals with different experiences, backgrounds and perspectives – particularly people of colour, LGBT+ and disabled people - because diversity of people and ideas remains integral to our excellence as a global civic institution.
Research Associate / Senior Research Associate in Biomolecular Statistical Analysis in London employer: University of Bristol
The University of Bristol offers an exceptional working environment for researchers in the field of biomolecular statistical analysis, fostering collaboration between leading international teams at both Bristol and UCL. With a commitment to flexible working arrangements, including hybrid options and part-time opportunities, employees benefit from a supportive culture that prioritises inclusivity and professional growth, allowing them to contribute to groundbreaking research while developing their skills in a dynamic academic setting.
StudySmarter Expert Advice🤫
We think this is how you could land Research Associate / Senior Research Associate in Biomolecular Statistical Analysis in London
✨Tip Number 1
Network like a pro! Reach out to researchers and professionals in your field on platforms like LinkedIn. A friendly message can go a long way in getting your foot in the door.
✨Tip Number 2
Prepare for those interviews! Brush up on your R or Python skills and be ready to discuss your past projects. Show them how you can tackle complex biomolecular datasets with ease.
✨Tip Number 3
Don’t underestimate the power of collaboration. Highlight your teamwork experiences in your conversations. This role is all about working with others, so let them know you’re a team player!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re serious about joining our awesome team at StudySmarter.
We think you need these skills to ace Research Associate / Senior Research Associate in Biomolecular Statistical Analysis in London
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your hands-on experience with R or Python in your application. We want to see how you've tackled complex datasets in your previous projects, so don’t hold back on sharing those details!
Tailor Your Application:Take a moment to customise your application for this role. Mention specific experiences that relate to biomolecular statistical analysis and archaeological research. This shows us you’re genuinely interested and have done your homework!
Communicate Clearly:Your ability to write and publish scientific manuscripts is key. Make sure your application is clear and concise, showcasing your communication skills. We love seeing well-structured applications that are easy to read!
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way to ensure your application gets to us directly. Plus, it makes the whole process smoother for everyone involved.
How to prepare for a job interview at University of Bristol
✨Know Your Stats
Brush up on your statistical analysis skills, especially in R or Python. Be ready to discuss specific projects where you've applied these tools to complex biomolecular datasets. This will show your hands-on proficiency and help you stand out.
✨Understand the Research Context
Familiarise yourself with the AquaNeo project and its objectives. Knowing how your role fits into the bigger picture of prehistoric diets and subsistence strategies will demonstrate your genuine interest and commitment to the research.
✨Prepare for Collaboration Questions
Since this role involves working with teams across Bristol and UCL, think of examples that showcase your collaboration and communication skills. Be ready to discuss how you've successfully worked with interdisciplinary teams or external partners in the past.
✨Showcase Your Creativity
Highlight any innovative statistical or analytical approaches you've developed. Prepare to discuss how these methods can be applied to archaeological and biomolecular data, as creativity is key in this role.