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data mining. The group provides a strong network to local AI expertise (e. g. Hessian.AI, TU Darmstadt), large scale compute infrastructure, as well as a broad international network (Stanford, UC San
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modelling Experience in programming (e.g. FORTRAN) Experience in the analysis of large data sets and/or the development of diagnostics Ability to work in a team, open-mindedness, and scientific creativity
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of Freiburg, founded in 1457, belongs to the best universities of Germany. Freiburg has a large international studen body and is located in the Black Forrest with a 30-minute drive to both Switzerland and
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, including but not limited to cancer, metabolic disorders, and infections. The research design involves the integration of large-scale biological datasets derived from both the host and the microbiome
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and disease risk factors Investigate new approaches in the analysis of large neurophysiological datasets We are seeking a highly motivated candidate with: A strong master’s degree in psychology
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want to contribute to tackling one of the big challenges of our time – then you may want to apply to the position in our team, which is expected to start on 01.11.2025. Appointment is conditional
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interdisciplinary team at the Technische Universität Dresden, focusing on the integration of multi-omics data to better understand, diagnose, and treat metabolic diseases (i.e. obesity, diabetes, metabolic
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cutting-edge big/deep data analysis methods, including machine learning and artificial intelligence. The ideal candidate will therefore have a strong background in data science and in the application and
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, diet, and immune system to investigate their roles in various diseases, including but not limited to cancer, metabolic disorders, and infections. The research design involves the integration of large
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extraction, sequencing library preparation, Hi-C, ATAC-seq etc.) Experience with bioinformatic analysis of large sequencing data sets Strong statistical skills using R Desirable: Experience with assembly