PhD Position: Spatio-temporal causal modeling of shared EV demand
Scholz Johannes
PhD Position: Spatio-temporal causal modeling of shared EV demand
100%, ETH Zurich, fixed-term
https://jobs.ethz.ch/job/view/JOPG_ethz_RlbuXptleQjHbM3L8g
ETH Zurich is one of the world’s leading universities specialising in science and
technology. It is renowned for its excellent education, its cutting-edge fundamental
research and its efforts to put new knowledge and innovations directly into practice.
The Institute of Cartography and Geoinformation is looking for a highly motivated
doctoral candidate at the Chair of Geoinformation Engineering, starting in January/
February 2026.
Project background
The research project “Estimating impacts of car-sharing vehicle and station alteration
on induced demand across spatio-temporal contexts”, funded by the Swiss Federal
Office of Energy, investigates how modifications in vehicle and station configurations
for shared electric vehicles (EVs) influence demand across different spatio-temporal
contexts. Shared EVs offer significant benefits for sustainable mobility and the
strategic placement of car sharing stations is crucial to maximize user adoption. Using
causal effect estimation and spatially aware predictive methods, tools will be
developed to simulate the impact of system changes in selected scenarios, supporting
the transition to a fully electric car-sharing service. These methods are adaptable to a
wide range of spatial decision-making problems by offering a framework to explore
“what-if” interventions across space and time.
The 3-year project will be carried out jointly by the Chair of Geoinformation
Engineering (Prof. Dr. Martin Raubal), the Department of Transport and Planning at TU
Delft, and Mobility Car Sharing.
Job description
The main objective of this PhD position is the investigation and application of methods
for evaluating the impact of changes in station or vehicle configurations on travel
behavior. The doctoral student will further estimate causal effects through predictive
machine learning models, and develop a generalizable decision-support system for
vehicle and station allocations. This research will be conducted together with domain
experts and collaborators.
The research will be linked to current topics and projects within the Mobility
Information Engineering lab and supervised by Prof. Dr. Martin Raubal (Chair of
Geoinformation Engineering). The position also includes teaching responsibilities
(20%) in courses offered by the Chair of Geoinformation Engineering.
Profile
– The ideal candidate must have an academic degree in Geoinformatics,
Transportation, Computer Science, or related fields, as well as a strong
research interest in (Spatial) Machine Learning
– Strong programming skills are required.
– The candidate must have excellent communication skills in English (oral and
writing)
– be team-oriented and willing to work in an interdisciplinary and international
environment.
– Knowledge of GIS
– German language skills (for teaching) are a significant plus.
ETH Zurich is one of the world’s leading universities specialising in science and
technology. We are renowned for our excellent education, cutting-edge fundamental
research and direct transfer of new knowledge into society. Over 30,000 people from
more than 120 countries find our university to be a place that promotes independent
thinking and an environment that inspires excellence. Located in the heart of Europe,
yet forging connections all over the world, we work together to develop solutions for
the global challenges of today and tomorrow.
In line with our values, ETH Zurich encourages an inclusive culture. We promote
equality of opportunity, value diversity and nurture a working and learning
environment in which the rights and dignity of all our staff and students are respected.
Visit our Equal Opportunities and Diversity website to find out how we ensure a fair
and open environment that allows everyone to grow and flourish. Sustainability is a
core value for us – we are consistently working towards a climate-neutral future.
We look forward to receiving your online application including the following
documents: letter of motivation, CV, short statement of research interests, full
academic records (such as Bachelor’s and Master’s degree transcripts), and names
and contact information of at least two references. Please note that we exclusively
accept applications submitted through our online application portal. Applications via
email or postal services will not be considered.
Review of applications will begin on 1st December, 2025, and continue until the
position is filled.
Questions regarding the position should be directed to Prof. Dr. Martin Raubal,
mra...@ethz.ch (no applications).
We would like to point out that the pre-selection is carried out by the responsible
recruiters and not by artificial intelligence.
Prof. Dr. Martin Raubal
ETH Zurich
Dept. Civil, Environmental and Geomatic Engineering
Institute of Cartography and Geoinformation
HIL G 37.3, Stefano-Franscini-Platz 5
8093 Zurich, Switzerland
www.raubal.ethz.ch, www.gis.ethz.ch
www.geogaze.ethz.ch, mie-lab.ethz.ch
www.rauming.ethz.ch, www.rauming.baug.ethz.ch
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Univ.-Prof. Dr.techn. Johannes Scholz
Paris-Lodron-University Salzburg
Schillerstrasse 30/I | 5020 Salzburg | Austria
Email:
johanne...@plus.ac.at |
>Study Geoinformatics in Salzburg - https://www.plus.ac.at/geoinformatik/studium/<