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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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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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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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onboarding period that includes specialized courses and hands-on training in AI and machine learning. You'll also have the chance to explore different labs and core facilities, meet fellow researchers, and
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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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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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, data scientific or machine learning background that is keen to work in an interdisciplinary environment and open to collaborating with researchers from other disciplines. The successful candidate will
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Bioinformatics, Computational Biology, Computer Science, Biomedical Engineering, Computer Engineering, Genetics/Genomics or related field experience with ‘omics platform output experience with biological datasets
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/or spatial multiomics, advanced imaging, iPS cells, machine learning, and computational biology. The ideal candidate will have a passion for addressing fundamental questions in biology and an eagerness
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theoretical methods shall be employed. A solid background in quantum mechanics and programming skills are prerequisite for this position, as is the readiness to learn and to apply new methods. For an initial