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Field
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, including tissue processing, molecular probe staining, and volumetric data acquisition using light sheet microscopes. The successful candidate will be a direct contributor to a large NIH UM1 research center
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workflows, and data engineering for mobility platforms • AI/ML for transportation prediction, system optimization, and environmental/health impact modeling • Deployment of decision-support tools for public
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to be developed: Implement and optimize inkjet printing processes using Fujifilm Dimatix printers, both in ambient and inert conditions. Optimize photochromic films printed on various substrates
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. Working closely with partners in the IMPRESS project, you will analyse their materials and provide valuable insights to help optimize device performance. Additionally, you will support collaborators by
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pillars such as Big Data Analytics and Management, Machine Learning and Optimization, AI for Data Science, Deep Learning, Generative Learning, Biometrics Processing, Natural Language Processing, Computer
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Area, and coordinated by Professor Alfeu Joãozinho Sguarezi Filho. The research is part of an international research network and involves geospatial analysis, optimization and modeling, as
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in engineering or a field related to the project; • Knowledge and proven expertise in computational optimization methods and discrete-event simulation, with experience in regular service design
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of chemically storing and releasing hydrogen, using methanol as a reservoir. Main activities: • Utilize global optimization codes and perform DFT calculations on supercomputers. • Analyze results and
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foundation. We are looking for a candidate excited by the challenge of rethinking data systems in the face of modern constraints such as optimization under uncertainty, constrained query evaluation
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and optimization of metasurfaces exhibiting tailored spectral responses at selected near-infrared wavelengths • Development of angularly robust optical functionalities over wide ranges of incidence