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Field
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and optimizing the execution User support in the field of large-scale AI Diving deep into technical aspects of efficiency, parallelization, and benchmarking Engaging in national and international ML/DL
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. The research group is seeking a talented Doctoral Researcher in nonlinear systems and control with strong interest in nonlinear stability theory, modeling & identification, optimal control, certifiably safe
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stability theory, modeling & identification, optimal control, certifiably safe & robust control, and learning for dynamics & control. The main task of the PhD student will be to develop sound data-driven
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. Secondly, we will evaluate the potential of a cladding-pumped Raman amplifier, once again seeking to optimize efficiency and gain equalization in the various cores by designing special optical fibers.Planned
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area of power systems with special interest in power system controls, protection, optimization, and AI/ML applications in power and energy systems. Experience with experiments and hardware-in-the-loop is
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Manufacturing and Process Optimization. Space and Harsh-Environment Materials Multifunctional and Bioinspired Systems. Requirements: Minimum: Ph.D. in Mechanical Engineering, Materials Science, Computer
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optimization of single-phase LCL filter inductors taking into account dynamic hysteresis models for different magnetic core materials. Supervisor: Prof. Paavo Rasilo (Electromechanics) Secondments: Université
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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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inactivation. Designing and optimizing multi-step and systems biocatalysis workflows, including flow chemistry and cascade reactions. Developing and applying modeling tools to evaluate kinetics, enzyme stability
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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