ID 2433: 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.

Possible topics could include (but are not limited to):

• Large-scale psychometric network analysis of acute psychosocial stress responses
• 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, including iOS app development, development of a Browser dashboard for real-time compliance tracking, etc.
• …

A selection of different projects in health psychology.

Tasks

• 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.
  • Web app development (JavaScript, node.js, React, etc.)
• German skills for supporting in data collection

Supervisors

Robert Richer, M. Sc.

PhD Candidate & Group Head

Luca Abel, M. Sc.

Researcher & PhD Candidate

Prof. Dr. Nicolas Rohleder

Chair of Health Psychology