Prof. Catherine Jutzeler, Ph.D.
Area of Interest
Data science, machine learning, medicine, neuroscience, medical devices
Prerequisites a student should comply with
The candidate should be interested in data science and its application to biomedical questions. Moreover, the candidate should have good understanding of interdisciplinary research is required. A solid understanding of mathematics and statistics is also required, while experience in coding (R or python) is an advantage but not a prerequisite.
Recommended master courses (Electives) of Learning Agreement of the Major
Human Health, Nutrition and Environment:
376-1719-00 Statistics for Experimental Research
376-1660-00 Scientific Writing, Reporting and Communication
227-0385-00 Biomedical Imaging
376-1306-00 Clinical Neuroscience
Neurosciences:
376-1719-00 Statistics for Experimental Research
376-1660-00 Writing, Reporting and Communication
376-1306-00 Clinical Neuroscience
227-1035-00 Dynamische Systeme in der Biologie
376-1307-22 Translational Neuroscience
Research projects of the group
- Prediction of disease progression (e.g., Alzheimer's disease, spinal cord injury)
- Identification of risk factors for the development of a wide range of diseases
- Data-driven biomarker discovery
- Data-driven drug repurposing strategies
- Data visualization (e.g., webapplications, shiny apps)