Postdoc: Wearable Health Data & PEM Analytics

Complexity Science Hub; Wien; Vor Ort; EUR 55.000 - 75.000; Vollzeit

Benefits dieser Stelle

Fully funded 2-year position

International team

Access to large-scale wearabledatasets

Professional development workshops

Training in ethical handling of real‑d

Zusammenfassung

Complexity Science Hub in Vienna invites applications for a two-year, fully funded postdoctoral researcher position within the TRACK-PEM project. You will develop and apply modern data science and machine learning methods to large-scale wearable health data to study PEM in ME/CFS and post-COVID condition.

The role emphasizes time-series analysis, methodological development, and collaboration across computational health, epidemiology, and clinical research, with opportunities for leadership and

Qualifikationen

• 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.
• Strong quantitative background and experience with statistical analysis, machine learning, computational modelling, or time-series analysis.
• 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.

Aufgaben

• Develop and apply modern data science and machine learning methods to large-scale longitudinal wearable and health data.
• Investigate whether patterns in wearable data can be used to identify and classify PEM and related health changes.
• Engage in methodological development and analysis of complex time-series data with attention to individual variability and real-world health data.
• Collaborate across researchers in computational health, network medicine, epidemiology, data science, and clinical research.
• Contribute to related research and develop collaborative methodological and scientific work within the wider group.

Kenntnisse

Quantitative background

Statistical analysis

Machine learning

Time-series analysis

Computational modelling

Python

R

Ausbildung

Doctoral degree in a quantitative field

Tools

Python

R

Jobbeschreibung

Complexity Science Hub in Vienna invites applications for a two-year, fully funded postdoctoral researcher position within the TRACK-PEM project. You will develop and apply modern data science and machine learning methods to large-scale wearable health data to study PEM in ME/CFS and post-COVID condition.

The role emphasizes time-series analysis, methodological development, and collaboration across computational health, epidemiology, and clinical research, with opportunities for leadership and