At the Institute of Sport Science of the University of Bern, a doctoral position is to be filled on November 1, 2024 (or by appointment) in the Department of Health Science with a focus on digital mental health interventions and depression within the project: Neurobiological and digital phenotyping towards digital mental health interventions in depression.
MASE is an ERA-NET NEURON-funded project which will set the basis towards evidence-based, tailored and expedient mental health interventions fostering primary and secondary prevention. Its multidisciplinary consortium of 5 European partners aims to apply brain network analyses to identify types of brains likely to profit from activity subjective energy association (ASEA); use artificial intelligence to identify where and when nonexercise activity helps people with certain brain properties; conduct an experimental study to test if the intervention suggestions found in step (a) and (b) really work out in everyday life; and develop and design a smartphone app that delivers ASEA interventions and provides suggestions when and where to engage in which short nonexercise activity to maximize participation rates. The University of Bern is primarily responsible for aim (c).
Tasks
* Develop phenotype tailored real-life smartphone interventions based on MRI, Accelerometry, Ambulatory Assessment/Ecological Momentary Assessment (AA/EMA) and just in time adaptive interventions (JITAI).
* Test the phenotype tailored real-life interventions using within person design.
* Collaborate with partners from other sites to develop and conduct the intervention.
* Work with the University of Bern Hospital (Insel) to recruit participants.
* Conduct fMRI, Accelerometry and AA assessments.
* Data collection, cleaning, preparation, and analysis.
* Participate in manuscript writing and publishing of measurement and data-based results.
Requirements
* Master's degree in behavioral or social sciences, informatics, psychology, sport science, or a related field.
* Committed to working across disciplinary boundaries.
* Good knowledge of statistical analysis (e.g., multilevel modeling).
* Basic training in fMRI scanning.
* Some knowledge of Ambulatory Assessment (AA).
* Some knowledge of Just-in-time adaptive interventions (JITAIs).
* Some knowledge of App development.
* Some knowledge of Accelerometry.
* Strong time and data management skills.
* Pro-active and self-motivated.
* Active participation in the workgroup.
* Very good English skills.
* At least basic German skills.
We offer
* Exciting and interdisciplinary project.
* Very good PhD supervision in an attractive and dynamic working environment.
* The position is limited to 3 years (possibility of extension by 1 year).
* Salary according to SNF guidelines.