Senior Research Associate: Artificial Intelligence for Ecology

Lancaster University; Bailrigg; On-site; GBP 40,000 - 46,000; Full time

Job summary

Lancaster University is recruiting a Senior Research Associate to advance AI methods for ecological monitoring within BEACON. You will work with ecologists and data scientists to push the boundaries of AI in underwater video analysis and contribute to a broader conservation toolkit.

You will hold a PhD in a relevant field, bring deep learning and computer vision expertise, and thrive in a collaborative, open-science environment that values reproducible research and impactful conservation

Qualifications

• PhD in computer vision, machine learning, AI or related discipline.
• Practical experience developing and applying deep learning approaches to real-world datasets.
• Familiarity with ecology or environmental science is advantageous but not essential.

Responsibilities

• Develop novel AI approaches for automated behavioural monitoring from underwater video.
• Collaborate with an interdisciplinary team to integrate AI with ecological experiments and models.
• Contribute to open science, reproducible research and responsible AI practices.

Skills

Deep learning

Computer vision

Edge AI

Interpretable AI

Education

PhD in computer vision, machine learning, AI or related discipline

Job description

Senior Research Associate: Artificial Intelligence for Ecology

Lancaster Environment Centre
Location: Bailrigg, Lancaster, UK
Salary: £39,906 to £46,049(Full time, indefinite with end date)
Closing Date: Sunday 13 September 2026
Interview Date: Friday 09 October 2026
Reference: 0755-26

Location: Lancaster. Travel for collaborations as required.

Contract length: 2 years 9 months.

We are seeking a highly motivated researcher to help shape the AI approaches within the broader scientific vision of BEACON (Behavioural Ecology AI for CONservation action), a new interdisciplinary research programme funded by UKRI. BEACON will develop the first integrated AI-enabled system for monitoring ecosystems and guiding conservation decisions through changes in animal behaviour. You will work closely with the PI (Dr Sally Keith), Co-I (Prof Chris Nemeth, Turing Fellow) and an interdisciplinary team to develop novel AI approaches for automated behavioural monitoring from underwater video, contributing across computer vision, machine learning, edge AI and interpretable decision-support systems. These methods will be integrated with ecological experiments and mechanistic models to create real-world conservation tools.

We are looking for someone with a strong technical foundation and curiosity about applying AI to complex real-world problems. You should have a PhD in computer vision, machine learning, AI or a related discipline, with practical experience developing and applying deep learning approaches to real-world datasets. Familiarity with ecology, animal behaviour or environmental science would be advantageous but is not essential. A commitment to open science, reproducible research and responsible AI principles is essential.

You will join a growing interdisciplinary team within the LEC-REEFS research group, linked strongly to the Data Science and AI Institute @Lancaster (DSAIL), working alongside behavioural ecologists, field ecologists and conservation practitioners. The project draws on an extensive archive of underwater video footage from the ReefRUV Network through Prof Sergio Floeter (Universidade Federal de Santa Catarina), and will collaborate with an international network of academic and conservation partners including Dr José Paula (University of Lisbon), the Seychelles Parks and Gardens Authority, Cefas, Natural England and Renew Earth. Dedicated training and mentoring will support the successful candidate in developing expertise in ecology, enabling them to work confidently at the interface of AI and conservation.

Lancaster University is a research-intensive university, ranked in the top 1% of universities globally and in the top 10 in the UK. Lancaster Environment Centre (LEC) is a large and multidisciplinary department tackling environmental challenges across the natural and social sciences, with strengths in high-diversity tropical systems. LEC offers a highly collegial and stimulating environment for career development based on departmental values and embedded Equality, Diversity and Inclusivity (EDI) considerations and actions. We are committed to family-friendly and flexible working policies on an individual basis as well as the Athena SWAN Charter, which recognises and celebrates good employment practice undertaken to address gender equality in higher education and research. Furthermore, we are active and progressive around sustainability, wellbeing and decolonising agendas.

EDI is strongly embedded within LEC-REEFS and DSAIL, and we actively work to create an inclusive environment where researchers from all backgrounds can thrive. We are particularly committed to improving diversity in AI and data science, and welcome applications from candidates who are underrepresented in these fields. We recognise that career paths are not always linear and welcome applications from candidates who have taken career breaks or worked outside academia. We also welcome informal enquiries about flexible working arrangements. Applicants from diverse backgrounds are strongly encouraged to apply.

We anticipate shortlisting in September 2026, with interviews shortly thereafter. The successful candidate is expected to start in Jan 2027.

Please note: unless specified otherwise in the advert, all advertised roles are UK based.

Find out what it's like to work at Lancaster University , including information on our wide range of employee benefits, support networks and our policies and facilities for a family-friendly workplace.

The University recognises and celebrates good employment practice undertaken to address all inequality in higher education whilst promoting the importance and wellbeing for all our colleagues.

We warmly welcome applicants from all sections of the community regardless of their age, religion, gender identity or expression, race, disability or sexual orientation, and are committed to promoting diversity, and equality of opportunity.