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research team. The following are considered as advantage: Any previous experience in working with spacecraft data. Deep knowledge of AI methods (esp. machine learning based) and their performance estimation
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pathway prediction. Apply deep learning techniques to predict reaction outcomes, optimize reaction conditions, and identify novel synthetic routes. Curate and manage reaction datasets from literature
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networks. The research will employ mathematical modelling and computer simulation to identify synaptic plasticity rules which enable effective learning in large and deep networks and is consistent with
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-energy molecules such as water, carbon oxides or N2 into fuels, chemicals and materials provides a promising alternative to the worldwide energy and environmental challenges. The postdoctoral researcher
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Number: 368999 The Department of Biomedical Engineering at the University of Minnesota is seeking a highly motivated Postdoctoral Researcher to join a dynamic team focused on developing intelligent
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learning at scale. Research directions include designing algorithms and methods for adaptive and personalised feedback, modelling learning behaviours with sequence and deep learning methods, and generating
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An exciting postdoctoral position is available in the exciting field of mathematics of deep learning, under the joint supervision of Prof. Alex Cloninger and Prof. Gal Mishne at UC San Diego. This NSF-funded
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Pharmaceutical health outcomes, (Pharmaco)epidemiology, Biostatistics, or a related field. · Expertise in or a strong interest in machine learning and deep learning algorithms. · Excellent communication skills
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related to staff position within a Research Infrastructure? No Offer Description About Us Are you a highly motivated postdoctoral researcher with a strong background in human immunology? We're seeking a
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interpretation through deep learning model development using Python and MATLAB. Why should I apply? Under the guidance of a mentor, you will engage in a variety of research activities, including: developing