Marc Weitz
Job description
Marc is employed as a doctoral research fellow at the Department of Computer Science and the High Northern Population Studies initiative were he works on new data science methods to process and model (raw) accelerometer data with special focus on the objective assessment of physical activity and lifestyle in large cohort studies (like the Tromsø Study).
Research interests
In his PhD Marc does research on new methods to process and model (raw) accelerometer data. These small sensors are often used to objectively meassure physical activity, sleep and other lifestyle factors in general in cohort and public health studies or as a control meassurement in experimental studies. Marc's research focuses on advancing our understanding of the collected data.
Teaching
Marc has been a teaching assistant for courses of the Health informatics and -technology (HIT) group. In the autumn semester 2021 he was a TA in the "INF-2710 Mobile health (mHealth) systems and applications", a course focusing on the theory and development of mobile health applications. In the spring semester 2022, he was a TA in "INF-3780 Computer Science Clinic – Physical and Virtual Environments" a master-level project-based course in which the students develop their own project within the field of medical informatics.
Member of research group
Member of project
CV
Marc Weitz is a doctoral research fellow in Computer Science at the arctic university of Norway in Tromsø (UiT). Prior to that he studied Cognitive Science at the university of Tübingen graduating in 2020 as a Master of Science (M.Sc.) with distinction. During his studies he worked part-time as a teaching asstistant of several undergraduate Computer Science and Cognitive Science courses and as a scientific software developer at the chair of Quantitative Linguistics headed by Prof. Harald Baayen where he developed the python package pyndl.