We are looking for a postdoctoral researcher to join the TRACK-PEM project, which investigates post-exertional malaise (PEM) in people with ME/CFS and post-COVID condition.
PEM is a worsening of symptoms following physical or mental activity. At present, PEM is mainly assessed through interviews and questionnaires, while objective measures that capture how it develops in daily life are still lacking.
The successful candidate will develop and apply modern data science and machine learning methods to large-scale longitudinal wearable and health data. A central aim of the project is to investigate whether patterns in wearable data can be used to identify and classify PEM and related changes in health. The work will involve methodological development and analysis of complex time-series data, with a particular focus on individual variability and real-world health data.
The successful candidate will be embedded in a research group dedicated to understanding healthcare systems as complex adaptive systems and will work closely with researchers across computational health, network medicine, epidemiology, data science, and clinical research. They will have opportunities to contribute to related research beyond the immediate TRACK-PEM project and to develop collaborative methodological and scientific work within the wider research group.
Postdoc Position: Wearable Data Analysis for ME/CFS and Post-COVID
Vienna
Full-time
Temporary
70,200 € per year
WE SEARCH FOR
YOUR PROFILE
- A completed doctoral degree or equivalent qualification in data science, statistics, mathematics, computer science, physics, biomedical engineering, bioinformatics, epidemiology, public health, or a related quantitative field
- A strong quantitative background and experience with statistical analysis, machine learning, computational modelling, or time-series analysis
- The ability to work independently, contribute methodological and scientific ideas, and collaborate effectively within an interdisciplinary research team
- Programming experience in Python, R, or a comparable language and an interest in health data, digital health, complex systems, or network medicine
- Proficiency in English
- Experience with wearable data, physiological signals, clinical research, ME/CFS, or post-COVID condition is advantageous but not required.
WE OFFER
- A fully funded 2-year postdoctoral position in an interdisciplinary and international research team
- The opportunity to work on an important and challenging health research project
- Access to clinical and large-scale wearable datasets
- Individualized guidance from an international team of advisors
- Scientific leadership and professional development workshops
- Practical experience aligned with career goals in academia, government, or industry
- Training in the ethical and technical aspects of working with real-world health data
APPLICATION
Please submit your application through this job platform.
Your application should include:
CSH is committed to equal employment opportunity. Employment decisions are based on the requirements of the position, qualifications, merit, and organizational needs. We encourage applications from groups that are underrepresented in science. Personal data are processed in accordance with applicable law and the CSH data protection policy.
Your application should include:
- Your CV (max. 2 pages)
- A cover letter explaining why you are interested in the project and how your background fits the position (max. 2 pages)
- List of selected research outputs such as publications, software, databases, dashboards, or other relevant work (max. 2 pages)
- Contact details for one academic or professional reference
CSH is committed to equal employment opportunity. Employment decisions are based on the requirements of the position, qualifications, merit, and organizational needs. We encourage applications from groups that are underrepresented in science. Personal data are processed in accordance with applicable law and the CSH data protection policy.
About us
The Complexity Science Hub (CSH) is Europe’s research center for the study of complex systems. We derive meaning from data from a range of disciplines – economics, medicine, ecology, and the social sciences – as a basis for actionable solutions for a better world. Established in 2015, we have grown to over 75 researchers, driven by the increasing demand to gain a genuine understanding of the networks that underlie society, from healthcare to supply chains. Through our complexity science approaches linking physics, mathematics, and computational modeling with data and network science, we develop the capacity to address today’s and tomorrow’s challenges.