Career

London School of Economics and Political Science – LSE Department of Geography and Environment

LSE is committed to building a diverse, equitable and truly inclusive university

Salary from £36,513 to £41,565 pa inclusive of London allowance

This is a fixed term appointment for 12 months with extension possible subject to Funding.

The London School of Economics and Political Science (LSE) is committed to building a diverse, equitable and truly inclusive university.

We are seeking a full-time Research Assistant (“pre-doc”) to work closely with Dr. Stephen Jarvis on a research project at the intersection of environmental economics and energy markets. The successful candidate will play an integral role in supporting data-driven, policy-relevant research examining energy markets and a range of associated social and environmental challenges. This role is ideal for candidates planning to apply to top PhD programmes and looking for hands-on research experience on high-impact questions in energy and environmental economics.

Key Responsibilities for the role include:

• Data collection, cleaning, and merging from large-scale microdata sources (e.g., electricity grid operational data, environmental emissions data, vehicle registrations, company accounts).
• Conduct data analysis using econometric and statistical tools (R and/or Python).
• Develop and conduct optimisation modelling (e.g. electricity market and grid dispatch).
• Assist in literature reviews and summarising academic research.
• Contribute to writing research papers and policy reports.
• Participate in meetings with collaborators and present research findings when appropriate.
• Support administrative and organisational aspects of research projects, as needed 

Essential Criteria

• Undergraduate or Master’s degree in Economics or another quantitative discipline, to be completed or close to completion by post start date.
• Advanced programming skills in R and/or Python.
• Willingness to learn unfamiliar tools as needed (e.g. GitHub, APIs, dispatch models).
• Familiarity with econometric techniques, especially panel data methods.
• Clear, concise written and verbal communication skills.
• Ability to work independently and manage time across multiple research tasks.

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