Technische Universität München

Job Description No matching  job preferences employment type working student Geometrical and topological machine learning techniques have established themselves as expressive techniques for extracting meaning from complicated data sets.   Recently, they have seen increasing use to characterize data sets in neuroscience, leading to stable representations.   In this project, we are interested in tackling the analysis of large-scale EEG and optical imaging data.   Finding common representations for these two data acquisition modalities will contribute new insights into the mind. We are searching for a student who wants to learn more about cutting-edge techniques in geometrical and topological machine learning.   The ideal candidate will already have knowledge about the Python programming language and is interested in answering scientific questions in an interdisciplinary team. Please apply to silviu.bodea@tum.de Contact: silviu.bodea@tum.de...