Salzburg Research and the Salzburg Ludwig Boltzmann Institute for Digital Health and Prevention closely collaborate at the interface of digitalisation, psychology, and health to enable sustainable and effective health promotion in prevention and rehabilitation through innovative solutions.
To strengthen our interdisciplinary research team, we are looking for a full-time position (for 3 years) with immediate effect.

PhD Student (w|d|m) - Data Engineer in Digital Health

With a focus on the development of digital health interventions that sustainably promote health-promoting behaviour. So-called adaptive interventions enable a high degree of personalisation and adjustment based on high-quality health and movement data in the context of "precision medicine".

Your Area of responsibility
- Further development of a data collection and data management platform for interdisciplinary research
- Joint development of new technical concepts for intervention options
- Testing and evaluation of digital sensor technology
- Deployment of (real-time) algorithms and AI models in models in productive systems
- Scientific work: publications, lectures, conferences in DE/EN

Your Qualifications
- A completed Master's degree in (medical) informatics, data science or a related field
- Good programming skills, ideally Java and Python
- Basic knowledge of data analysis, e.g., with R, Matlab, etc.
- Ideally experience in the health and/or medical sector or relevant technologies (e.g., the processing of high-frequency sensor data)

The monthly salary is EUR 3,163.16 gross for a 38.5-hour week, analogous to the FWF model.
Further information and benefits: www. .at /career
Please send your application with the identification [DOK-Engineer] to: [log in to unmask] 

We look forward to hearing from you!

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