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Field
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sensors - if we can control and tune their properties. You will develop and use top-of-the-line machine learning models to predict the sensor response of these materials under realistic conditions
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neuroimaging methods to better detect disrupted function following neonatal brain injury, and identify new more energy efficient learning algorithms that could reduce the economic and environmental cost of AI
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, and machine-learned force fields to describe ion transport and interfacial evolution. These models will be extended to mesoscopic and continuum scales (kinetic Monte Carlo, phase-field) to capture
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, machine learning, molecular dynamics, and fluid mechanics. We aim to understand how chemical structure of precursors and process conditions affect film quality, helping design better materials and
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neuroscience, brain circuit imaging and atlas mapping, and machine learning and AI - that will expand a cross-college team studying the brain circuits underlying craving, reward, and addiction. The hire will
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Neuroscience. This position is one of four within a coordinated cluster hire - alongside colleagues in brain circuit imaging, machine learning and artificial intelligence, and research software engineering
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and Atlas Mapping. The position is one of four in a coordinated cluster hire - alongside colleagues in behavioral neuroscience, machine learning and AI, and research software engineering - studying
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The faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) uses mathematics, electronics and computer technology to contribute to the development of Information and Communication Technology
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environment for doctoral researchers interested in longitudinal and mixed-methods approaches to language learning and mobility.
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concepts about biological processes, advance information technologies and human-machine interactions and, last but not least, provide new insight for designing efficient strategies for teaching and learning