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analysis of large data sets, statistical modeling, and knowledge of at least one programming language (e. g.: R, Python and/or Julia) are required. Experience in machine learning and image recognition
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enable the model to infer health-related information directly from NMR spectra of human blood. To this end, the model will be pre-trained using self-supervised learning on large-scale, partly synthetic
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The Institute for Infection Prevention and Control (IPC, Head Prof. Dr. Philipp Henneke) is looking as soon as possible for a Bioinformatician (m/f/d, PhD) with focus on the analysis of large
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for a PhD student to join our team and help us make exciting new advances in applications of machine learning (ML) strategies for analyzing X-ray and neutron scattering data! You will be working in a
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information science techniques. Several areas of computer science and mathematics play important roles: data management and engineering, machine learning and data analytics, signal and image processing
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Your Job: In this position, you will be an active part of our Simulation and Data Lab for Applied Machine Learning. Within national and European projects, you will drive the development of cutting
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. - Neural networks and machine learning strategies for the analysis of scattering data. Large amount of scattering data obtained in our group requires development of the advanced analysis techniques. In
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, medical informatics, databases, data mining, machine learning, applied mathematics, biomedical modelling and analysis of complex networks. Joint data science projects between the different partners
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organisation To achieve valuable scientific results, talented PhD students need to acquire knowledge and are also required to exchange knowledge and experience with other PhD students in method-oriented working
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networks and machine learning strategies for the analysis of scattering data. Large amount of scattering data obtained in our group requires development of the advanced analysis techniques. In this project