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Field
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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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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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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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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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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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Microplate, droplet, cell-free, or growth-coupled systems UPLC, LC, and GC-MS based screening assay development Automation and data-driven optimization Biochemistry and Chemical biology Design, synthesis, and
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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
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staff position within a Research Infrastructure? No Offer Description The selected candidate will develop innovative and efficient resource optimization algorithms, suitable for this context, with cost
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-21-CE08-007 ended in March 2025). The work in N POLAR will focus on the development and optimization of this innovative process (hybrid semiconductor/metal/semiconductor heterostructures) in order to