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implement optimal experimental approaches for molecular scale quantum sensing Co-supervise and guide younger project students at the BSc, MSc and PhD level Maintain a thriving laboratory culture, ensuring
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CO2 capture from the atmosphere. Your objectives will include to: Develop new optimization and/or machine-learning based reconstruction and segmentation algorithms to improve image quality in time
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carrier and its various transport transitions stochastically. The PhD student will join the LUMIN team that is pushing the boundaries of luminescence physics. The researcher will collaborate with other team
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primary role will be to contribute to project tasks that demand a deep understanding of electrical or thermal energy system operation and dynamics, modelling approaches, and optimization methods. To excel
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, holistic planning and scheduling to optimize resilience across several factory systems. Development of AI-based tools and complex simulation systems is expected to be a core contribution. 3) IT and OT
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hubs. Control and optimization of power electronics for flexible port energy systems. Modeling, simulation, and experimental validation of port power conversion and electrification solutions. Integration
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tasks will consist of: Brainstorming and designing how to handle samples for multiple analysis. Optimization of protocols for tissue preparation before further analysis of disease mechanisms (and drug
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The aim of the project is to generate De novo enzymes to degrade PET from composite fibers from recycled textiles. The first-generation designs will be further optimized after experimental
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mathematical and analytical models to predict coil loss, facilitating the optimal design of HPMCs Constructing a large-signal platform to measure coil loss of HPMCs Exploring innovative solutions, such as new
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industrial and academic partners. The overall goal of the project is to optimize the design of water eletrolyzers for efficient green energy production. You will be conducting Computational Fluid Dynamic (CFD