Highlights
Find out more aboute the specialties of our program below!
Statistical Practice in Clinical Research (STA 490)
In the Statistical Practice in Clinical Research module our students work on real-world projects selected from the Clinical Research Methods Division of the Division of Biostatistics. Supervised by a senior statistician they write a reproducible report and present their results to the clients as well as their fellow students. Through this course, students gain experience in the statistical problems encountered in clinical research and at the same time train their communication and reporting skills. Many of the projects lead to publications (List of publications from projects).
Good Statistical Practice (STA 472)
It is very important to us that our students become not only well versed in statistical methodology, but also acquire the technical and communication skills that are important for a good statistician. A particularly important concern is reproducible research. In our compulsory course Good Statistical Practice we teach a variety of topics, such as:
- R Markdown
- Dynamic reporting
- Git
- Efficient programming
- Containerization
- Scientific Writing
- Presentation skills
Are you interested in learning more about reproducibility? Check out the Center for Reproducible Science.
Introduction to Machine Learning (ML) in Biomedicine (BME 338)
As one of the elective modules, we strongly encourage our students to choose Introduction to Machine Learning (ML) in Biomedicine. This module covers supervised learning, unsupervised learning, neural networks, and deep learning — always with a focus on their application in biomedicine. Ethical considerations and the interpretability of machine learning are also integral parts of the module.