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Field
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(AIMLeNS) lab is a tight-knit team of computer scientists, chemists, physicists, and mathematicians working collaboratively. Our focus is on developing practical methods that blend traditional disciplines
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to the engineering process, ensuring it is current and usable for informed decision-making in circular economy contexts. The research group studies how technology impacts organizations using mixed methods—both
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Chalmers University of Technology focused on the recycling of carbon fibre composites. The project aims to develop a novel method for recovering fibres using magnetic fields, with the goal of lowering
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, vortex matter, matter at ultra-high pressure, diagrammatic Monte-Carlo. We are interested in analytical and numerical approaches to fermionic and bosonic states. Examples of one of the directions in our
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computational simulation techniques are used. The research is applied to understand orthopaedic problems and to develop better methods to improve tissues regeneration. The group encompasses about 15 scientists
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, we conduct successful medical research and hold the largest range of medical education in Sweden. At KI, you get to meet researchers working with a wide range of specialisms and methods, giving you
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research group that views automation engineering as a key enabler for new methods and applications, driving and benefiting from the ongoing digitalization of society. Our research emphasizes social, economic
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the work will be detailed catalyst characterization. A wide range of methods will be used, including XRD, BET, SEM, TEM, TPR, TPD, DRIFT, and XPS. Atom Probe Tomography (APT), with sample preparation
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the duties. The overarching goal of this research program is to uncover fundamental molecular principles governing membrane protein function, particularly how interactions with subunits, auxiliary proteins
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changes and established markers for Alzheimer's disease. The project may also include machine learning methods to estimate individuals' biological age. The project is based on existing data from a prominent