Research Associate

About us

School VI Medicine and Health Sciences encompasses the areas of human medicine, medical physics and acoustics, neuroscience, psychology, and health services research. Together with the four regional hospitals, School VI forms the University Medicine Oldenburg. Furthermore, there is close collaboration with the University Medical Center of the University of Groningen.

Your tasks

The advertised position aims at developing methods for data-driven analysis of activity trajectories, which encompass various input modalities. A particular focus will be on data from motion sensors, which must first be appropriately aggregated over time to relate them to other types of data collected in the project (functional parameters and social activities). For this purpose, pre-trained models (Foundation Models) will be employed. In a second step, changes in activity profiles will be characterized and modeled. Methods of explainable AI (XAI) should also be used for this purpose. The data analysis should be carried out in close coordination with the other project partners of the subproject, and therefore the work has a strongly interdisciplinary character. Research results, both methodological and applied, should be published in professional journals and presented at relevant conferences.

Your profile

Requirements

• Completed university degree in Computer Science, Mathematics, Physics, or related fields
• Excellent command of English, both written and spoken
• Theoretical and practical knowledge (the former demonstrated through relevant courses/completed online courses, the latter demonstrated through personal projects) in the field of machine learning, especially in the area of deep neural networks
• Very good programming skills in Python and in the Machine Learning framework PyTorch
• High degree of independence, flexibility, and teamwork skills, as well as willingness to work in an interdisciplinary manner

Desirable

• Knowledge of German
• Experience with physiological time series, especially with data from motion sensors (demonstrated through completed courses or personal projects)
• Experience with scientific presentations and publications

We Offer

• A diverse, stimulating, and challenging field of activity
• An open, creative, and dynamic work environment in the divisions "AI4Health" and "Assistance Systems and Medical Technology"
• The opportunity for self-directed work
• Support for young researchers (e.g., through training and development opportunities)
• Flexible, family-friendly working hours
• VBL supplementary pension in the public sector

Our standards

The University of Oldenburg is dedicated to increase the percentage of female employees in the field of science. Therefore, female candidates are strongly encouraged to apply. In accordance to § 21 Section 3 NHG, female candidates with equal qualifications will be preferentially considered. Applicants with disabilities will be given preference in case of equal qualification.

Further information

The position is part of a project funded by the Federal Ministry of Education and Research (BMBF) titled "Intersectoral Care for Older People: Ensuring Treatment Success after Hospital Stay". The advertised position will focus on analyzing physical and social activity trajectories of older people in inpatient settings and home environments. The project is embedded in the framework project "Intersectoral Care for Vulnerable Groups".

The division "AI4Health" is headed by Prof. Dr. Nils Strodthoff. The division "Assistance Systems and Medical Technology" is headed by Prof. Dr. Andreas Hein.

There is an opportunity for further academic qualification (doctorate).

Contact:

If you are interested or have questions, please contact Prof. Dr. Nils Strodthoff (nils.strodthoff@uni-oldenburg.de