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models. The scientist will conduct research using machine learning and classical parameterization methods on data from ocean gliders equipped with microstructure turbulence sensors, turbulence resolving
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reliable machine learning-based surrogate models to replace expensive phase field models to simulate failure because of HE. The activities will be complemented by own lab testing e.g., SSRT incl
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highly motivated doctoral student to join an ambitious project aimed at building machine and deep learning models to study the genetics of human disease. Funded as part of the Helmholtz AI program, the
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information systems engineering. The group conducts research on the application and the impact of digital technologies like DLT/Blockchain, Digital Identities, Machine Learning/AI, GenAI, and IoT/5G
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Information Systems engineering. The group conducts research on the application and the impact of digital technologies like DLT/Blockchain, Digital Identities, and Machine Learning/AI 5G on organisations from
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, Bioinformatics, Epidemiology, Biostatistics, Biomedical Sciences, or related disciplines; Strong background in statistical modeling, and/or machine learning (any experience in multimodal AI is an asset); Previous
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, memristive devices), and the evaluation with e.g. machine learning and image processing benchmarks Requirements: excellent university degree (master or comparable) in computer engineering or electrical
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problems in biology by combining machine learning with in-depth knowledge of biological processes. Who we are looking for You have a Master in Science (Bioengineering, Biochemistry-Biotechnology, Biomedical
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include previous research in computational modeling, machine learning applications in genomics, protein structure, participation in bioinformatics projects, or hands-on experience with AI tools applied
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communications Data Analysis and Management Implement and open-source proof-of-concept software tools Machine learning is a plus Strong analytical and programming skills are required (Python, Matlab, and C/C