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

Research Initiative in Data-Driven Policy Optimization

Join the esteemed Group for Sustainability and Technology (SusTec) at ETH Zurich, where we delve into the intersection of policy, technology innovation, and organizational strategies aimed at achieving a decarbonized energy system and fostering a circular economy.

Project Background

In response to the rapid transformation of energy and transportation systems concerning climate change, our initiative seeks to harness innovative tools to support policymakers in balancing overarching transition goals with community impacts. This project will focus on developing insightful methods that merge machine learning with energy system optimization, facilitating the creation of effective policies that govern electric vehicle (EV) charging and the broader electricity system.

• Investigate policies surrounding EV adoption, charging infrastructure, and electricity pricing.
• Evaluate systemic impacts including cost, CO2 emissions, and community benefits such as improved air quality.

Research Expectations

We anticipate a commitment to rigorous scientific research that retains relevance for policymakers and industry leaders. As a key contributor, you will collaborate within our group and engage with various stakeholders, disseminating your findings through high-impact peer-reviewed journals and outreach platforms. Additionally, you will have the opportunity to mentor master’s students and provide support for teaching initiatives.

Candidate Profile

The ideal candidate should possess the following qualifications:

• M.Sc. or equivalent in engineering, computer science, data science, or a related discipline
• Outstanding academic performance
• Strong analytical abilities with a passion for sustainability and public policy
• Interest in ongoing political and societal discussions
• Ability to work independently while managing multiple tasks
• Team-oriented with excellent communication skills
• Proficient in coding (e.g., Python) with coursework in optimization or machine learning
• Fluent in both spoken and written English

Preferred qualifications may include:

• Experience in energy or transportation modeling and research
• Relevant work experience
• Prior scientific publications in related fields
• Knowledge of energy and transportation sector transitions

Research Environment

We offer a vibrant, supportive research atmosphere within a cutting-edge academic institution. You'll engage with top-tier researchers while working alongside a diverse and dynamic team. Your day-to-day guidance will be provided by Dr. Siobhan Powell, with leadership from Prof. Volker Hoffmann.

This initiative is fully funded, and you will be appointed as a full-time researcher for the project's duration (spanning from 2025/2026 to 2029/2030). Your competitive annual remuneration will align with ETH Zurich regulations. This position is based in Zurich, Switzerland, and remote work from outside the country is not feasible due to legal requirements.

Diversity and Inclusion

ETH Zurich is dedicated to fostering an inclusive culture that promotes equal opportunity, values diversity, and creates an environment where all individuals are respected. Our commitment to equity is fundamental to our institutional values.

Explore Opportunities

We invite you to consider this enriching research opportunity. Further information regarding our initiatives can be found on our website. We look forward to your engagement with this promising research direction.