Postdoctoral Researcher in Applied Machine Learning for Digital Health and Digital In-Vehicle Biomarkers

Job title:

Postdoctoral Researcher in Applied Machine Learning for Digital Health and Digital In-Vehicle Biomarkers

Company

ETH Zürich

Job description

DruckenOver 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 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 backgroundConsidering these challenges, we are looking for a personality with a strong will to create a meaningful impact. We aim to design, implement, and evaluate a cannabis-impaired driving detection and prevention system within the Revelio initiative. Building upon previous studies that have been well-recognized for their contributions (ETH medal, CHI Best Paper Award), we will 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 descriptionThe work will contribute to the broader field of digital health. Accordingly, we offer the position of a Postdoctoral Researcher at the Department of Management, Technology, and Economics (MTEC) at ETH Zürich within the . You will lead the Revelio initiative and co-supervise two PhD students in close collaboration with Prof. Elgar Fleisch (ETH Zürich) and Prof. Felix Wortmann (University of St. Gallen). The project is funded for 3 years by the Swiss Road Safety Fund (Fonds für Verkehrssicherheit) and will be conducted 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. ETH Zürich offers a highly competitive salary and outstanding working conditions.As part of an interdisciplinary team at the intersection of applied machine learning, behavioral science, forensic toxicology, and automotive safety, you will contribute to developing robust, real-time models for detecting and preventing impaired driving. Your work will be key in integrating novel in-vehicle sensing approaches and AI-driven interventions into next-generation automotive systems. To ensure real-world impact, your research must address critical challenges such as model generalization, adversarial robustness, and regulatory compliance, paving the way for adoption by automotive manufacturers and stakeholders, including Swiss and international road safety authorities.You will also engage in promotional activities to increase community awareness of your work through conferences, workshops, keynotes, seminars, and social media engagement, while also working on grant proposals, study protocols and publications for high-quality, peer-reviewed outlets (e.g., ACM Conference on Human Factors in Computing Systems, Lancet Digital Health, npj Digital Medicine). You will also be involved in teaching activities.ProfileWe are looking for candidates with the following qualifications:

• A PhD in Computer Science, Information Technology, Information Systems, Statistics, Data Science, Engineering, or a related field
• Expertise in machine learning and (health) interventions (preferred)
• Strong interest in interdisciplinary collaborations; prior experience is a plus
• Strong interest in applied science
• Familiarity with ethical, legal, and health-political challenges of interventional research
• Strong verbal and written communication skills in English

WorkplaceWorkplaceWe offer

• Your job with impact: Become part of ETH Zurich, which not only supports your professional development, but also actively contributes to positive change in society
• We are actively committed to a sustainable and
• You can expect

, such as public transport season tickets and car sharing, a wide range of sports offered by the , and attractiveWe value diversityIn line with , 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 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:

• A motivation letter
• CV
• Transcripts
• List of publications (including “under review” and “forthcoming” manuscripts)

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 ( ).About ETH ZürichETH 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.

Expected salary

Location

Zurich

Job date

Wed, 21 May 2025 06:50:12 GMT

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