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difference in the areas of materials and manufacturing, we look forward to receiving your application. About the research project The position is focused on development of robust AM and post-AM processing
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for industrial application. You will develop materials and processes enabling this technique to be scaled up and implemented globally. The research includes optimization of the electrochemical processes
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screening approaches. The PhD student will develop and apply analytical workflows to characterize complex food matrices. The project includes i) developing and optimizing screening workflows; ii) improving
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to the development of several innovative doping methods. More broadly, the research aims to understand and control how molecular interactions, ions, and charge transfer processes determine the electronic properties
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for users to conduct their experiments. We strive to ensure that the beamtime is used optimally and that all users have the support they need to successfully complete their experiments. Our goal is to make a
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real computational problems that cannot be efficiently solved on a conventional computer. Such computationally hard problems are found, e.g., in optimization, quantum chemistry, materials science
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, incorporating their own ideas and experience in computer vision, machine learning, and related fields, to further visualization and interpretation of molecular images. Our research environment focuses
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to be employed for the degradation and mineralization of per- and polyfluoroalkyl substances (PFAS) in water streams. At KTH, the focus is on the design, fabrication, and optimization of cavitation
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Optimal Transport for Optimization and Machine Learning Appl Deadline: 2026/02/04 11:59PM (posted 2025/12/19, listed until 2026/02/04) Position Description: Apply Position Description Doctoral student in
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provide insights into where energy expenditure is highest and where efficiency improvements can have the greatest impact. By doing so, this work aims to contribute to a better understanding and optimization