PhD Position in Applied Computer Science and Machine Learning for Digital Health and Digital In-Vehicle Biomarkers

100%, Zurich, fixed-term

Over the last few decades, the prevalence of drug-induced fatal car accidents has drastically increased. In the US, for example, the National Highway Traffic Safety Administration (NHTSA) reports that 56% of the injured or killed roadway participants were tested positive. Thereby, the most prevalent drug was cannabis with 25%. Since the legalization of cannabis is currently globally progressing, urgent measures are needed to prevent a highly likely increase of such accidents.

Project background

In light of these challenges, we are looking for a personality with a strong will to create a meaningful impact. Our goal is to design, implement, and evaluate a cannabis-impaired driving detection and prevention system. Building upon previous studies that have been well-recognized for their contributions (ETH medal, CHI Best Paper Award), we will first conduct a real-world study in which subjects are put under the influence of cannabis while performing a pre-driving test and a driving task on a test track. We then develop and evaluate a robust cannabis-driving detection model before and while driving. Ultimately, we are working towards a scalable digital biomarker platform for in-vehicle driver state detection, contributing to the long-term goal of Vision Zero (eliminating traffic-related fatalities and severe injuries).

Job description

The work will contribute to the broader field of digital health. Accordingly, the position at ETH Zürich is embedded within the Centre for Digital Health Interventions and is co-supervised by Prof. Elgar Fleisch (ETH Zürich) and Prof. Felix Wortmann (University of St. Gallen). The project is funded by the Swiss Road Safety Fund (Fonds für Verkehrssicherheit) and in close collaboration with Prof. Wolfgang Weinmann (Forensic Toxicology, University of Bern). The position is set to begin on July 1st, 2025, with flexibility regarding the start date.

Profile

We are looking for candidates with the following qualifications:

A master’s degree preferably in Computer Science, Information Technology, Information Systems, Statistics, Data Science, Engineering, or a related field
Strong machine learning and programming experience with the ability to work across frontend, backend, and embedded environments
Strong conceptual and communication skills, especially when presenting research findings to diverse, interdisciplinary audiences
A collaborative mindset and willingness to work in an interdisciplinary team
Excellent organizational skills, attention to detail, and the ability to work independently
Proficiency in both English and German (C1/C2, written and spoken)

Workplace

We offer

Contribute to a mission-driven research project at the intersection of technology, public safety, and healthcare innovation:

Join a dynamic team of motivated young researchers in a collaborative and supportive environment
Typical PhD duration: 3 to 3.5 years with guaranteed funding throughout
Competitive salary and excellent working conditions by ETH Zürich standards
Access to state-of-the-art infrastructure and resources within a leading research institution
Take on direct responsibility for both data gathering (manage vehicle, medical devices, frontend and backend systems) and ML development
Direct project responsibility and close collaboration with renowned research partners, including leading universities, automotive companies, and startups

Working, teaching and research at ETH Zurich

We value diversity

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.

Curious? So are we.

If you are interested in the position and would like to be part of a highly motivated, young team, we would be pleased to receive your online application, including the following documents:

CV
Transcripts
A motivation letter
Written references from previous supervisors are encouraged

Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services cannot be considered.

Questions regarding the position should be directed to Prof. Dr. Felix Wortmann (felix.wortmann@unisg.ch).

About ETH Zürich

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.