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feedstocks. ACCELERATE gathers leading academics and industries that want join forces. Within this effort, this position will focus on the engineering, analysis, and optimization of catalytic reactors
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systems. This PhD project, part of a national initiative, aims to use AI to design and optimize thermal interface materials (TIMs). It combines machine learning, materials informatics, and experiments
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computing, with a focus on performance analysis, development, and optimization of scientific simulation codes. The work involves applications in plasma physics, computational fluid dynamics, and molecular
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mathematics, such as extreme value theory, inference for stochastic processes, optimization theory, and/or Monte Carlo simulations. Experience in obtaining research grants in national and/or international
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Doctoral student in materials chemistry with focus on electrolyte design for Mn-based flow batteries
capacity degradation. The work duties include: design electrolyte and additives to optimize electrochemical performance, enhance stability, and extend battery lifespan. perform electrochemical
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of numerical modelling (e.g. CFD, FEA, FSI, optimization, ML), but we are also involved in experiments and real-life monitoring to support our findings. Besides research, our division is actively involved in
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. Methods from probability theory, communication theory, electromagnetics, optimization and machine learning will play an important role. We are ultimately looking to either one of the two broad research
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communication theory, array signal processing, optimization, and machine learning will likely play a vital role. The research will mainly be theoretical, but KTH has testbeds for potential experiments. However
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the purpose of developing a model to predict CRUD-composition and stability on the basis of water chemistry and thereby identify optimal conditions. We are looking for a person with a strong background in
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temperature thermal energy storage and integrated systems. The doctoral student will have a broad perspective focusing on technological development, laboratory testing and techno-economic analysis to identify optimal