At a Glance
- Tasks: Join a groundbreaking project analysing biodiversity impacts from climate policies.
- Company: Imperial Business School, a leading institution in environmental economics.
- Benefits: Competitive salary, 41 days off, career development support, and a generous pension scheme.
- Other info: Full-time role with opportunities for promotion and a collaborative work culture.
- Why this job: Make a real difference in environmental policy while advancing your research career.
- Qualifications: PhD in relevant field, strong data analysis skills, and proficiency in R or Python.
The predicted salary is between 49017 - 57582 £ per year.
Location: South Kensington Campus
About this role
The Centre for Health Economics & Policy Innovation (CHEPI) at Imperial Business School is recruiting a Research Associate to join an exciting interdisciplinary project at the frontier of environmental economics and biodiversity science. Governments around the world are regulating greenhouse gas emissions — but the wider ecological consequences of these policies remain poorly understood. This Royal Society-funded project will deliver the first causal and monetised estimates of biodiversity impacts arising from the EU Emissions Trading System (EU ETS), embedding findings within a planetary health framework that connects climate policy, air quality, and ecological change. You will be supervised by Dr Laure de Preux (Imperial Business School) and Dr Will Pearse (Department of Life Sciences), working across disciplinary boundaries to produce research that is both scientifically rigorous and directly relevant to policymakers.
What you will be doing
- Integrate and harmonise large-scale biodiversity, environmental, and industrial emissions datasets across Europe
- Apply causal inference methods to identify the impact of EU ETS regulation on local co-pollutant emissions
- Develop species distribution models and analyse biodiversity responses to policy-induced environmental change
- Contribute to the economic valuation of biodiversity outcomes within a planetary health cost-benefit framework
- Produce academic publications, policy briefs, and reproducible research outputs for scientific and policy audiences
What We're Looking For
We are seeking a quantitative researcher with:
- A PhD (or equivalent) in biodiversity science, environmental science, geospatial modelling, data science, or a related quantitative field.
- Strong experience with large, complex spatial or environmental datasets
- Proficiency in R or Python and strong quantitative modelling skills
- Ability to analyse complex data and produce clear, policy-relevant insights
- Excellent written and verbal communication skills, with the ability to disseminate research findings to diverse audiences
*Candidates with a PhD near to completion will be considered for appointment as a Research Assistant, with promotion on successful completion.
What We Can Offer You
- The opportunity to continue your career at a world-leading institution and be part of our mission to continue science for humanity.
- Grow your career: gain access to Imperial’s sector‑leading dedicated career support for researchers as well as opportunities for promotion and progression.
- As a member of research staff you have 10 development days to use to develop your skills and explore your career prospects.
- Sector‑leading salary and remuneration package (including 41 days off a year and generous pension schemes).
- Be part of a diverse, inclusive and collaborative work culture with various staff networks and resources to support your personal and professional wellbeing.
Further Information
This post is Full‑Time and Fixed Term initially for 22 months, with an anticipated start date of around October 2026. Interviews will be conducted online in early July 2026.
For informal enquiries, please contact: Dr Laure de Preux (LdePreux@imperial.ac.uk) or Dr Will Pearse (Will.Pearse@imperial.ac.uk).
£49,017 to £57,582 per annum
Research Associate in Biodiversity and Pollution Modelling employer: Imperial College London
Imperial Business School offers an exceptional work environment for the Research Associate in Biodiversity and Pollution Modelling, situated at the prestigious South Kensington Campus. Employees benefit from a sector-leading salary, generous leave, and a strong focus on professional development, including dedicated career support and 10 development days to enhance skills. The inclusive and collaborative culture fosters innovation and well-being, making it an ideal place for researchers passionate about impactful environmental economics and biodiversity science.
StudySmarter Expert Advice🤫
We think this is how you could land Research Associate in Biodiversity and Pollution Modelling
✨Tip Number 1
Network like a pro! Reach out to professionals in the biodiversity and environmental science fields on platforms like LinkedIn. Join relevant groups, attend webinars, and don’t be shy about asking for informational interviews. We all know that sometimes it’s not just what you know, but who you know!
✨Tip Number 2
Prepare for those interviews! Research the latest trends in biodiversity and pollution modelling, especially related to EU policies. We recommend practising common interview questions and even doing mock interviews with friends or mentors to boost your confidence.
✨Tip Number 3
Showcase your skills! Create a portfolio of your work, especially any projects involving R or Python. Highlight your experience with large datasets and quantitative modelling. We want to see your best work, so make it easy for potential employers to see what you can bring to the table!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are genuinely interested in joining our mission at StudySmarter. Don’t miss out on this opportunity!
We think you need these skills to ace Research Associate in Biodiversity and Pollution Modelling
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter for the Research Associate role. Highlight your experience with biodiversity science, environmental datasets, and any relevant projects that showcase your quantitative skills. We want to see how you fit into our mission!
Show Off Your Skills:Don’t hold back on showcasing your proficiency in R or Python! Include specific examples of how you've used these tools in past projects. We love seeing clear, policy-relevant insights derived from complex data, so make that shine through.
Communicate Clearly:Your written communication skills are key! Ensure your application is well-structured and free of jargon. We’re looking for clarity and conciseness, so make it easy for us to see your potential impact on policymakers and the scientific community.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets to the right people. Plus, you’ll find all the details you need about the role and our team!
How to prepare for a job interview at Imperial College London
✨Know Your Stuff
Make sure you brush up on the latest research in biodiversity and environmental economics. Familiarise yourself with the EU Emissions Trading System and its implications. Being able to discuss recent studies or findings will show your passion and expertise.
✨Showcase Your Skills
Prepare to demonstrate your proficiency in R or Python during the interview. You might be asked to solve a problem or explain how you've used these tools in past projects. Bring examples of your work that highlight your quantitative modelling skills.
✨Communicate Clearly
Since you'll need to convey complex ideas to diverse audiences, practice explaining your research in simple terms. Think about how you would present your findings to policymakers or the general public. Clear communication is key!
✨Ask Insightful Questions
Prepare thoughtful questions about the project and the team. This shows your genuine interest in the role and helps you understand how you can contribute. Ask about the interdisciplinary nature of the work and how it impacts policy-making.
