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inorganic AEMWEs by integrating the perovskite electrolyte with perovskite electrodes from cell fabrication to cell configuration optimization and to single cell performance. Significance The project has
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to: - Developing underwater communication systems using deep learning which are well-performing to nonlinear channels. - Establishing a deep learning architecture which is optimal for underwater acoustic
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. David Marlevi, Prof. Ulf Hedin, and Dr. Ljubica Matic to improve stroke risk prediction for patients with carotid atherosclerosis using a multidisciplinary combination of data-driven imaging
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for 2-3 PhD students interested in using real-world data to inform the pricing, reimbursement, and optimal use of healthcare technologies. This unique opportunity allows for cutting-edge research in
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Applications are invited for a position in the rapidly expanding data analytics run by Prof Adam Dubis. The main focus of the team is to develop deep learning tools for prediction of disease progression
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of these oat cultivars in ruminant diets will be addressed and the main objective is to ensure optimal utilization of oats in the diet, and thereby to ensure that oats strengthen its position as a highly
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, environmental, climate and animal welfare impacts, the idea that alternative proteins can replace meat is generating hype, optimism and substantial investments. Whether involving insects, plants, lab-grown meat
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Regular Job Code 9742R5 Employee Class Acad Prof and Admin Add to My Favorite Jobs Email this Job About the Job Required Qualifications: * Ph.D. or Masters with equivalent experience in Computational
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of dehydration using a low-power radio-frequency (RF) sensor. The research objectives include design optimization to improve wearability, robust data acquisition using machine learning and establishing correlation
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proteins can replace meat is generating hype, optimism and substantial investments. Whether involving insects, plants, lab-grown meat or other ingredients, alternative proteins come with high expectations