Postdoctoral Researcher (80-100%)

The Digital Humanities Lab at the University of Basel is looking to hire a postdoc in the research group led by Prof. Rosa Lavelle-Hill, which focuses on applications of Artificial Intelligence (AI) in the social sciences, as of 1st August 2026, or by arrangement.
The position is embedded in a large interdisciplinary research project, ICARUS, that investigates individual vulnerability, behavioral change, climate change attitudes, and risk under environmental heat stress by combining psychological profiling, biological lab data, physiological time series, and sensor data. The postdoc will play a leading role in developing and implementing predictive algorithms designed to identify those most at risk from extreme heat, as well as offering personalized adaptation advice --- translating rich multi-modal data into interpretable, scalable prediction and advising models.



The position is part of a larger interdisciplinary project, ICARUS, which will study the interactions between physiology, psychology, and culture to improve the mitigation of health threats associated with global warming. Combining expertise in physiology, pharmacology, photobiology, psychology, behavioral science, and AI, the project aims to develop an improved framework for identifying individuals at risk but also for improving advice adherence and effective risk mitigation measures. We also investigate how an individual's heat adaptation relates to attitudes on climate change. Other collaborators and members of the ICARUS project are Professor Lars Nybo (University of Copenhagen), Professor Andreas Flouris (University of Thessaly), and Associate Professor Catharina Lerche (Bispebjerg Hospital, Copenhagen).

Your position

• Developing machine-learning prediction models for individual-level risk prediction using heterogeneous data (psychological and biological profiles, ecological momentary assessment (EMA), and time series sensing data)
• Applying, evaluating, and comparing supervised and unsupervised methods (e.g., regularized regression, tree-based models, ensemble methods, clustering, dimensionality reduction) and deep learning approaches
• Developing and applying explainable AI (XAI) methods to ensure interpretability and to gain insights from the data
• Translating predictive models into algorithmic "advising” or warning frameworks, balancing accuracy, interpretability, and scalability
• Collaborating closely with psychologists, physiologists, and other heat domain experts to ensure that models align with theoretical constructs and applications
• Leading and co-authoring high-quality scientific publications
• Designing and contributing to open, reproducible, and well-documented research pipelines and code bases

Your profile

• A completed PhD in data science, computer science, statistics, computational social science, economics, quantitative psychology, or a closely related field
• Expertise using machine learning
• Ability to work with high-dimensional and/or longitudinal data
• Excellent critical programming skills in Python
• Strong command of English (spoken and written)
• Familiarity with ethical and responsible AI considerations
• Interest in translating models into applied or decision-support tools

• Experience in harmonizing different types of datasets
• Experience with explainable AI or interpretable machine-learning methods
• Experience with psychological questionnaire data and/or biological measurement data
• Comprehension of the German language

We offer you

• A full-time 80-100% postdoctoral position for at least 18 months with the possibility of extension to the end of the project.
• An intellectually stimulating research environment with strong international and interdisciplinary connections
• Close collaboration with researchers across psychology, physiology, and data science
• Support for publications, conference participation, and career development activities
• Employment conditions according to the regulations of the University of Basel