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/thesis: Industry-/collaboration PhD student in optimized off-road driving in forests Research subject: Soil science Description: We are looking for an industry/collaboration-based PhD student to develop a
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, to automation and optimization, machine design, production, and production systems. Project Description This PhD project is part of the research project “Sustainable and Resilient Hydrogen Infrastructure
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organization and management, innovation and entrepreneurship, and industrial and social marketing in technology- and innovation-intensive activities, to automation and optimization, machine design, production
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the real world based on a seamless combination of data, mathematical models, and algorithms. Our research integrates expertise from machine learning, optimization, control theory, and applied mathematics
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principles for transceiver frontend design, including data converter solutions. Expected outcome is a disruptive and novel approach to co-optimized radio transceiver design with measured and verified state
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. Within this platform, the ADME of Therapeutics (ADMEoT) — also known as Uppsala University Drug Optimization and Pharmaceutical Profiling (UDOPP) — operates as a specialized unit in the Department
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known as Uppsala University Drug Optimization and Pharmaceutical Profiling (UDOPP) — operates as a specialized unit in the Department of Pharmacy, Faculty of Pharmacy. The unit focuses on in vitro ADME
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Advanced Grant to determine the optimal combination of epitopes that elicits the highest level of protection. Within the research group, we value a positive work environment built on respect and
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material layers that can be optimized to specific battery chemistries and flow phenomena from the microscale up. The developed technologies will be validated in half-cells and full working batteries
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affordable and durable long-duration energy storage. The approach is to use hierarchical structures, i.e. complex material layers that can be optimized to specific battery chemistries and flow phenomena from