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Field
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machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run
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networks (5G and WiFi 7 and their evolutions) in terms of architecture, protocols, and optimization. These networks benefit from new technologies and approaches, such as virtualization and AI, to make them
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circularity by optimizing the recovery of critical raw materials in the hydrometallurgical recycling of Li-ion batteries. In this reserach, you will: Investigate purification and separation methods
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related to staff position within a Research Infrastructure? No Offer Description The aim of the project is to develop and optimize an innovative method for utilizing new ultracold, strongly polar, and
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, and power systems planning. The candidate will develop a novel modelling framework that translates climate signals to support cost-optimal long-term investment decisions, while also considering
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PhD degree in Physics, Materials Science, Electrical Engineering, Nanotechnology, or a related field. o Strong hands-on experience in cleanroom micro- and nanofabrication, ideally using Silicon
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medicine, with a primary focus on optimizing clinical trial design. The partnership will bring together the University of Oxford’s expertise in statistics, mathematics, engineering and AI with industry
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this process. To facilitate the removal, we can optimize the surface active chemistry such that the system is more prone to destabilize. When several chemistries are present this becomes very challenging and
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medicine, with a primary focus on optimizing clinical trial design. The partnership will bring together the University of Oxford’s expertise in statistics, mathematics, engineering and AI with industry
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graphene-based field effect transistor sensors with biological receptors for infection biomarkers, and optimize this technology for diagnosing infections in the wound settings. As a postdoctoral researcher