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Field
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materials for new products, and optimizing manufacturing processes Responsibilities R&D: Lead material selection, development, and characterization for applications in electronics, aerospace, or biomedical
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The University of British Columbia (UBC) | Vancouver UBC, British Columbia | Canada | about 19 hours ago
tumours, allowing advanced immunotherapies to reach and treat cancer. The Faculty of Pharmaceutical Sciences strives to enact this vision by supporting the optimization of drug therapy in pursuit
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protein foods including through high moisture extrusion. Key responsibilities will include: Explore innovative methods for food process optimization including the use of AI and machine-learning Develop and
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structure–activity relationships (SAR) to optimize the potency, physicochemical and ADME properties, pharmacokinetics, safety, and in vivo efficacy of lead molecules. In collaboration with other scientists
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integrating advanced Artificial Intelligence (AI) and Machine Learning (ML) techniques with process-based crop models, this research will empower farmers to optimize conservation practices, increase
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structures at the atomic level, conducting failure analysis, selecting materials for new products, and optimizing manufacturing processes Responsibilities R&D: Lead material selection, development, and
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implementation of elastomer adhesives Optimization of formulation for 3D printing and 2D printing Contribute to ongoing ionic liquid formation projects Design and prototype and scalable processing Collaborate with
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for understanding how AI-enabled control, optimization, and market design can support large-scale decarbonization, grid modernization, and the integration of distributed and flexible energy resources. Research topics
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interdisciplinary scholarship and be excited about substantial conversation and collaboration with other disciplines. This postdoctoral fellowship program aims to create a cohort of researchers optimally positioned
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, drastically reduce emissions and waste, and maximize material quality and circularity. The project integrates a digital thread for real-time process optimization, advanced sensors for contaminant detection