Tasks:

• Conduct research on adaptivity and personalization of digital and mobile health technologies, including applications of recent advances in machine learning and artificial intelligence
• Research practical data analytics strategies for a long-term integration of multiple data-streams, including continuous sensor data
• Design studies and accompany the implementation of digital health systems
• Conduct research on technology-assisted behavior change and decision support systems
• Contribute to the development of a user-friendly mHealth platform
• Collaborate in clinical studies of novel technology-assisted interventions
• Work collaboratively in a highly interdisciplinary and international team
• Co-supervise PhD-candidates, master students and interns
• Lead on – and contribute to – collaborative, interdisciplinary publications and proposals

Qualifications:

• PhD and portfolio of internationally recognized (English language) publications in the areas of (applied) data science and/or (digital health) multi-device systems engineering
• Expertise in software development, ideally including backend and/or middleware, as well as experience with (near-)real-time data processing and analytics
• Expertise in methods and conduct of system evaluations and studies
• Experience in data analytics with longitudinal / timeseries data
• Experience with machine learning / artificial intelligence for personalization and/or adaptive systems and/or user modeling
• Independent work style and high self-motivation
• Interest in complex and challenging tasks and topics
• Excellent problem-solving skills, flexibility, resilience, and teamwork ability
• Excellent conduct of the English language; German skills welcome but not strictly required

Details:

Work hours: 40 hours per week (lower percentage can be subject to negotiation)
Location: Ludwig Boltzmann Institute for Digital Health and Prevention at the University Hospital of Salzburg (SALK), Lindhofstrasse 22, 5020 Salzburg, Austria
Earliest start: 2024 April 01; post can be filled as soon as a viable candidate is found
Duration: 24 months (2 years)

For informal queries please feel encouraged to contact Dr.-Ing. Jan Smeddinck: wna.fzrqqvapx@quc.yot.np.ng
Please send your application including CV, three selected publications, as well as optionally a portfolio of your research, implementation, and/or other work and project experiences in any format (PDF, GitHub, website, etc., links to common trusted cloud storage providers are fine for larger file sizes) to bssvpr@quc.yot.np.ng. (Application documents can optionally be encrypted using the PGP key at: https://drive.google.com/file/d/1kKxtvtURRHqfq8seTTVxV1hzScDgQ6Yf.)