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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | about 3 hours ago
-scale assimilation Develop new interfaces between PDAF and different data assimilation systems of project partners and to machine-learning based assimilation methods Extend the ensemble assimilation
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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. Become a part of our team and join us on our journey of research and innovation! Be
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Science, Computer Science, Data Science, Neuroscience, or a related field by the start date. Demonstrated expertise in computational modeling of human behavior or computer vision / machine learning
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. Emphasis is placed on artificial intelligence/machine learning approaches applied to digital data and multi-omics data. Additional responsibilities include mentoring students, collaborating with faculty
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materials using statistical mechanics, molecular simulations, and machine learning. Expectations Candidates will be responsible for: Developing multi-scale modeling methods for polymeric materials, using
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disciplines. Familiarity with contemporary AI systems (e.g., machine learning, generative models) at a conceptual or applied level. Experience with qualitative or mixed research methods (e.g., ethnography
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fellows will receive joint mentorship from leading experts in metabolic biology, AI and machine learning, drug delivery, and translational medicine, while maintaining full academic independence in research
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: Prior experience running behavioral experiments is desirable, as is previous collaboration or engagement with researchers in economics. Familiarity with methods from machine learning will be a plus. All
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, marital status, military status, national origin, parental status, partnership status, predisposing genetic characteristics, pregnancy, race, religion, reproductive health decision making, sex, sexual
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new insights into the phenomena observed and enrich the databases required for deep learning methods. The neural networks currently being developed at LISTIC to detect and segment areas of movement in