470 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"U.S" positions at Nature Careers
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Are you interested in neuromorphic spintronic and can you contribute to the development of the project? Then the Department of Electrical and Computer Engineering invites you to apply for a one year
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, machine learning, and causal inference frameworks that link genetic variants to cellular mechanisms and therapeutic opportunities. Our research spans immune biology, cardiac disease, neurodegeneration, and
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computational tools (e.g. machine learning, artificial intelligence or other approaches) are also encouraged to apply. You will teach pharmacology-related courses in the Bachelors of Life Sciences, Medicine
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Postdoc (f/m/d) Leader of Junior Research Group "WEEE-Recycling" / Completed university studies (...
-hand experience in the application of machine learning, simulation and modelling concepts in resource technology # Proven track record of interdisciplinary collaboration along the value chain of raw
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sciences or equivalent (M.Sc. or Ph.D). Experience with C# and Python programming (async/multithreading) languages. Experience with real-time programming. Experience with machine learning, big data, signal
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paraganglioma driven by cell plasticity using spatial transcriptomics and machine learning.” High-risk neuroblastoma (NB) and malignant paraganglioma (PPGL) are neural crest–derived tumors with pronounced
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collaboration across disciplines, strengthens partnerships with industry and society, and nurtures a thriving global network, who spearheads advancements in AI & Machine Learning, Data Science, Environmental
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(postdoc) Limited until: 31.08.2026 Reference no.: 4943 Explore and teach at the University of Vienna, where over 7,500 brilliant minds have found a unique balance of freedom and support. Join us if you’re
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various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly
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understanding of the terrestrial water cycle, particularly of the flood risk system Experience in statistical data analysis, machine learning and AI-based modelling Experience in research software development and