WE ARE HIRING!

We are looking for a PostDoc to develop novel machine learning methods pertaining to various problems in mammographic data analysis. More details can be found here.

We are looking for an administrative employee to perform typical secretarial duties at TU Berlin. (Full job description can be found in the links: in Deutsch, in English)

We are looking for a research assistant to work on various topics around the analysis of uncertainty in data, as well as benchmarking, software development, and to help with administrative processes.  (Full job description can be found here: uncertainty in data)

For the upcoming WS23/24, we offer the following courses:

• Uncertainty in Machine Learning (Moses, ISIS)
• Topics in Biomedical Data Science (Moses, ISIS)
• Programming Lab for Undergraduates (BSc level Programmierpraktikum): Quality Data Science (Moses, ISIS)

The Machine Learning and Uncertainty group 8.44 develops and validates machine learning techniques with applications in neuroscience and medicine. Current research interests include  

• Solutions to the brain's electromagnetic inverse problem using Bayesian methods 
• Brain functional connectivity analysis using electro- and magnetoencephalography 
• Interpretation/explanation of machine learning models  
• Creation of synthetic reference datasets and benchmarking procedures to assess quality aspects of computational methods  
• Uncertainty estimates for inverse problems 

Current applications include 

• Diagnosis and characterization of psychiatric and neurological disorders 
• Intensive care unit (ICU) data 
• Brain-computer interfaces 

The group is tightly linked with the Brain and Data Science Group at Charité - Universitätsmedizin Berlin and the Department of Uncertainty, Inverse Modeling and Machine Learning at Technische Universität Berlin, both also led by Dr. Stefan Haufe.