Research Associate: Marine Ecology & Conservation (Fixed Term)

Economics Network; United Kingdom; Remote; GBP 42,000 - 60,000; Full time

Benefits offered by this job

Flexible working arrangements

Job summary

The University of Cambridge invites applications for a Research Associate in the Marine Ecology and Conservation Group within the Department of Zoology. The successful candidate will develop and apply high-resolution, simulation-based stock assessment approaches to tuna fisheries and related populations.

You will work with population modelling and demographic analyses, contributing to methodological advances and evidence-based management advice, with opportunities for collaboration and data

Qualifications

• PhD in marine ecology or a related field.
• Experience with population modelling and stock assessment methods.
• Strong data analysis and programming skills in R or Python.
• Experience with fisheries data and modelling applications.

Responsibilities

• Develop and apply high-resolution, simulation-based stock assessment approaches.
• Integrate models to evaluate population biology and fisheries data influence.
• Collaborate with international stock assessment community.
• Contribute to evidence-based data collection and advice for management.

Skills

Population modelling

Statistical analysis

Quantitative ecology

Fisheries science

Education

PhD in Marine Ecology or related field

Tools

Stock Synthesis (SS3)

SPoRC framework

R

Python

Job description

A Research Associate post is available in the Marine Ecology and Conservation Group, led by Dr Catharine Horswill, in the Department of Zoology at the University of Cambridge. Catharine is a quantitative marine ecologist with expertise in population modelling, demography and the application of ecological evidence to conservation and management.

Reliable stock assessments are essential for the sustainable management of tropical tuna fisheries worldwide. In representing complex population and fishery dynamics, assessment models rely on simplifying assumptions about biological processes, spatial structure and fisheries data. Understanding how these assumptions affect model performance and management advice is critical for identifying key sources of uncertainty and determining where methodological advances or improvements in fisheries data could most effectively strengthen future assessments.

The project will develop and apply high-resolution, simulation-based approaches to evaluate how assumptions about population biology and fisheries data influence stock assessment performance and management advice. The project will initially focus on Indian Ocean yellowfin tuna, with subsequent application to bigeye and skipjack tuna where appropriate.

Initial work will build on an existing high-resolution, spatially explicit simulation framework developed using the Spatial Population Model (SPM). SPM will be used to generate population and fishery scenarios that incorporate key sources of structural uncertainty, including spatial variation in growth and fishery selectivity, alternative population structures, and differences in the weighting of fisheries data. Assessment models, including Stock Synthesis (SS3) and next-generation platforms such as SPoRC https://chengmatt.github.io/SPoRC/, will then be fitted to these simulated datasets to evaluate how different sources of uncertainty influence assessment performance and management-relevant outputs. This project will identify where methodological developments or improvements in the resolution of fisheries data could most effectively strengthen future tuna assessments. The project will also evaluate the potential of emerging monitoring and data-collection approaches to resolve key uncertainties and improve assessment performance, including genetic, age-composition and fisheries-independent data.

The project aims to deliver both methodological advances in fisheries stock assessment and practical evidence to support future assessments and priorities for data collection. Through close engagement with the international stock assessment community, the research is intended to inform the development and application of future tropical tuna assessments and strengthen the evidence base for fisheries-management and catch advice.

The position is funded by the Sustainable Fisheries and Communities Trust https://sfact.org/.

For more information, please refer to the Further Particulars document.

Deadline for applications is midnight on 30th September 2026. Interviews are due to be conducted during the week commencing 19th October 2026 (subject to change)

Fixed-term: The funds for this post are available for up to 24 months.

Part-time working or other flexible working arrangements will be considered.

For informal enquiries about the role, please contact Dr Catharine Horswill [email: [e-mail]].

For any queries regarding the application process, please contact the Zoology HR Office [email: [e-mail]]

Please quote reference PF50942 on your application and in any correspondence about this vacancy.

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.

The University has a responsibility to ensure that all employees are eligible to live and work in the UK.