ID 2327: Various Topics for Machine Learning and (Web) App Development in Health Psychology
Bachelor’s / Master’s Thesis / Research Internship / Project
The aim of our research is to explore the potential of digital technologies in psychological research to better understand human psychology and behavior. Many psychological research areas still rely on “traditional” methods, such as laboratory protocols or the collection of self-reports or obtrusive, often invasive biomarkers which lack of digital solutions and might limit the advancements of these areas. Thus, our goal is to tackle this issue by working at the intersection of technology, health, and psychology. The research projects of our group include the development of mobile apps, wearable and contactless sensing paradigms, machine learning algorithms, or other digital platforms that can assist in the assessment, induction, or intervention of various psychological states.
We always have open topics for various types of theses in our research area. Have a look at our group page to get a more detailed picture of our projects and previous student theses in our research area.
Possible topics could include (but are not limited to):
- Further development of stress+, a web application for acute remote psychosocial stress induction
- Development of a web interface for processing physiological data using BioPsyKit – an open-source package for the analysis of biopsyschological data
- Extending the CARWatch framework for robust and reliable cortisol awakening response (CAR) assessment
If you are interested in working with us, please use the application form to apply and tell us which topics you would be most interested in. We will then get in contact with you and together, we can identify a suitable topic for you.
- You will work in an interdisciplinary team with psychologists and engineers
- You have the opportunity to apply your data science knowledge to practical applications in stress research
- Depending on the topic and scope of your project, you will:
- Support in data collection
- Implement different algorithms into an existing data analysis framework
- Perform statistical and machine learning-based data analysis
- Document your code in a clear and structured manner
Requirements (depending on the topic and type of project)
- Interest in diving into the field of acute stress responses and psychology (especially biopsychology, psychophysiology, and psychoneuroendocrinology)
- Knowledge in data processing, data analysis, and data visualization using Python (or willingness to learn such!)
- Further skills:
- Knowledge of machine and deep learning, (Bayesian) statistics, etc.
- German skills for supporting in data collection
Robert Richer, M. Sc.
PhD Candidate & Group Head
Luca Abel, M. Sc.
Researcher & PhD Candidate
Prof. Dr. Nicolas Rohleder
Chair of Health Psychology
Please use the application form to apply for the topic. We will then get in contact with you.