PhD Student in Data-Driven Policy Optimization for Transportation and Energy

Project Background

Our energy and transportation systems are rapidly transforming in the fight against climate change. Policymakers need new tools to help balance the transition's big-picture objectives with the systems' impacts on people and communities.

This project will contribute new tools and insights for the optimal design of policies that affect electric vehicle (EV) charging and the electricity system. The focus will be on the development of innovative methods that integrate machine learning with energy system optimization to facilitate effective policy optimization.

The analysis will encompass policies for EV adoption, EV charging infrastructure, and electricity pricing, considering both system-level impacts on cost and CO2 emissions and community-level impacts such as improvements in air quality.

Role Overview

Expectations include delivering scientifically rigorous research that holds relevance for policymakers and managers. Collaboration with colleagues, engagement with policymakers, and interaction with various stakeholders will be key aspects of the role. Publication in high-impact, peer-reviewed journals and outreach outlets is a fundamental responsibility, alongside the supervision of master’s students and support for teaching within the group.

Candidate Profile

The ideal candidate should possess the following qualifications:

• Hold an M.Sc. or equivalent degree in engineering, computer science, data science, or a closely related discipline.
• Demonstrate an excellent academic record.
• Exhibit strong analytical skills.
• Show passion for sustainability, energy, and public policy.
• Be engaged in current political and societal discussions.
• Exhibit independence while managing multiple tasks and deadlines.
• Possess effective teamwork and communication skills.
• Have experience with coding (e.g., with Python).
• Have completed courses in optimization, machine learning, or similar fields.
• Be fluent in spoken and written English.

Additional desirable qualifications include:

• Experience with energy or transportation modeling or research.
• Relevant work experience.
• Prior scientific publications in related areas.
• Knowledge of the energy and/or transportation sectors and their transitions.

Work Environment

A positive research environment awaits, situated within a large, dynamic team at a globally leading academic institution. The role presents opportunities for frequent interactions with leading researchers in the vibrant community of energy system research at ETH Zurich and beyond.

Your day-to-day work will be supervised by Dr. Siobhan Powell, with Prof. Volker Hoffmann leading the research group.

Funding and Location

This PhD project is fully funded, with the successful candidate being hired as a full-time researcher for the project duration (2025/2026 to 2029/2030). The starting date is negotiable, with efforts to fill the position as soon as possible (late 2025 - early 2026). The annual salary is highly competitive in accordance with ETH Zurich regulations, and the position is located in Zurich, Switzerland. Please note that remote work from outside of Switzerland is not permitted due to legal constraints.

Diversity and Inclusion

ETH Zurich promotes an inclusive culture that encourages equality of opportunity and respects the rights and dignity of all staff and students. The institution values diversity and nurtures an environment where everyone can grow and flourish.

Curiosity and Engagement

We look forward to the prospect of your involvement, contributing to impactful research within a collaborative and innovative environment.