Address: Medizinische Fakultät
Geissweg 5/1
72076 Tübingen


Contact person

frontend.sr-only_#{element.icon}: Brigitte Lindenbauer


frontend.sr-only_#{element.icon}: +49 7071 29-77915


frontend.sr-only_#{element.icon}: brigitte.lindenbauer@med.uni-tuebingen.de


Data Scientist

Data Scientist

Data Science is an interdisciplinary field of science that develops quantitative methods, processes, algorithms and systems for extracting insights, patterns, and inferences from both structured and unstructured data.

Medicine is one scientific domain that is increasingly benefitting from data science approaches. Technological advances in the fields of life science and medicine result in large volumes of medical data generated and stored in hospitals every day. This includes biological material, genetic and non-genetic health-related data (real-time values such as blood pressure or pulse, blood values, MRI data or answers to surveys, health status, disease-specific mortality rates, etc.).

Data science offers physicians the opportunity to interpret large amounts of such complex data, in particular to the end of prevention, observation, diagnosis and treatment of patients, as well as medical research and development, and this progress is expected to continue in the future. Thus, not only the medical staff, but above all the patients are expected to benefit from these ongoing developments.

The Talent Academy aims at fostering careers of data scientists in the field of medicine, as well as of physicians conducting research using data science. To this end the Talent Academy focuses primarily on supporting (cross-faculty) networks that are designed to connect the two disciplines.

Upcoming networking events

The Data Scientist Symposium will take place on Monday, October 6, 2025. The agenda will be published as soon as possible.

 


Data Scientist Symposium

Opening hours: Monday, October 6, 2025 from 09:30 am - 05:00 pm

Address: Conference Center Schnarrenberg, building 520

What you need in your career as a data scientist

Being a data scientist in a medical environment requires a range of special skills and competencies. The adjacent list provides an overview classified into different career stages and the applicable categories: compulsory (C), recommended (R), and optional (O).

Our tip: check our Event Database to see if a suitable course is listed for your needs.