PhD Student in Transportation and Energy: The Group for Sustainability and Technology (SusTec) at ETH Zurich is offering a fully funded PhD position focused on the optimization of policies related to transportation and energy systems, specifically in the context of climate change and sustainability.
PhD Student in Data-Driven Policy Optimization for Transportation and Energy
Designation
PhD Student in Data-Driven Policy Optimization for Transportation and Energy (100%)
| Field | Details |
|---|---|
| Research Group | Group for Sustainability and Technology (SusTec) |
| Institution | ETH Zurich |
| Employment Type | Full-time, Fixed-Term |
| Duration | 2025/2026 to 2029/2030 |
| Salary | Competitive (per ETH Zurich regulations) |
| Starting Date | Late 2025 – Early 2026 (negotiable) |
Research Area
The research will focus on the integration of machine learning with energy system optimization, aiming to enhance policies for electric vehicle (EV) adoption, charging infrastructure, and electricity pricing while considering broader impacts on CO2 emissions and community health.
Location
Zurich, Switzerland
Eligibility/Qualification
- Degree: M.Sc. or equivalent in engineering, computer science, data science, or related fields.
- Skills:
- Strong analytical skills
- Experience in coding (e.g., Python)
- Knowledge in optimization, machine learning
- Interest: Passionate about sustainability, energy, and public policy.
- Languages: Fluency in spoken and written English.
- Preferred (not required): Experience with energy/transportation modeling, prior scientific publications.
Description
The PhD position will involve close collaboration with researchers, policymakers, and stakeholders in a vibrant academic environment. You will publish your findings in high-impact journals, support teaching, and supervise Master’s students. The research aims to produce methods that facilitate optimal policy design concerning EV infrastructure and electricity systems, addressing both systemic costs and community health outcomes.
How to Apply
Interested candidates should submit the following documents through the online application portal:
- CV with contact details of two referees
- A letter of motivation detailing research interests and reasons for applying
- BSc and MSc transcripts
- An example of written work (e.g., master’s thesis)
Note: Applications via email or postal service will not be accepted.
Last Date to Apply
September 12, 2025 (Applications will be reviewed on a rolling basis starting from late August 2025; early applications are encouraged as the position may fill before the deadline.)
