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must be met no later than the time the employment decision is made. At least three of: (stochastic) partial differential equations ((S)PDEs) graph theory/network science stochastic optimization and
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programme. Requirements: Education: PhD in chemistry, chemical engineering, materials science, biochemistry or equivalent. Knowledge: Extensive expert use of an array of physicochemical and materials
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manuscripts, grants and train undergraduates in the lab is desired. PhD in a biomedical science such as physiology, exercise science, pharmacology, or immunology earned by the start date. Research experience in
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requirements, what we are really looking for is a creative, quantitatively strong scientist who likes to invent. Your PhD might be in physics, computer science, computational or systems biology, bioinformatics
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. Experience applying machine learning to networking problems, for example, reinforcement learning, graph neural networks, or uncertainty quantification. A track record of publications in leading networking
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Foundation Health Model. As a PhD candidate, you will conduct deep-dive research into training pipelines and reasoning techniques for clinical foundation models. You will join an elite, interdisciplinary team
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. Experience applying machine learning to networking problems, for example, reinforcement learning, graph neural networks, or uncertainty quantification. A track record of publications in leading networking
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Physics, Spectral Theory, Quantum Chaos, Large Graphs and Quantum Walks. Related areas such as Quantum Information can also be considered. This position is offered through the research funds of Mostafa
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candidate is self-motivated and hard-working with a PhD in Data Science, Computational Social Science, Computer Science, or Information Science, with no more than five years post receipt of the PhD
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and Experience PhD, MD, or equivalent doctoral degree in Neuroscience, Biomedical Engineering, Computer Science, or a related field. Candidates in ABD (all but degree) status will also be considered