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Nursing (MSN), Doctor of Nursing Practice (DNP), and PhD in Nursing. Our programs are designed to meet the evolving demands of today’s healthcare landscape, equipping graduates with rigorous training
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. This interdisciplinary position sits at the intersection of robotics, machine learning, and sustainable chemistry. You will join a vibrant research environment at the University of Liverpool, building upon our team's
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(postdoc) Reference no.: 6036 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 passionate about
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to learn about, (road) network traffic flow theory and simulation. You are interested in mentoring and supporting MSc and PhD students. You are a machine learning enthusiast (and realist). You love coding
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IOCB Prague (Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences) | Czech | 2 months ago
across European life-science AI efforts. Requirements PhD in computational biology, bioinformatics, machine learning, or a related computational field Hands-on experience with foundation models / large
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, or machine learning) Experience working with various animal models Ability to work in an interdisciplinary research environment Specific Requirements Programming experience (Python and R) Experience with
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shortly) a PhD in Immunology, or other relevant discipline in Biomedical Sciences, and a BSc (hons) in a relevant Biological Science. Extensive and up-to-date theoretical and practical knowledge in
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and experiences. You should demonstrate: Essential Criteria: Hold (or expect to hold shortly) a PhD in Immunology, or other relevant discipline in Biomedical Sciences, and a BSc (hons) in a relevant
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groups from Stanford and beyond working on complementary approaches to T cell recognition. Our group provides an intellectually rich environment, with scientists applying genetics, proteomics and machine
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),. Familiarity with data analytics, machine learning, digital twin knowledge, or Python programming language. Knowledge of additive manufacturing, process physics, thermodynamics, and/or metallurgy to interpret