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Field
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research on raw materials, materials, processes, and systems to contribute to the sustainable development of forest resources and a circular bioeconomy. The department is located on campuses in both Umeå and
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for Communication Systems carries out research, undergraduate and postgraduate education in communications engineering, statistical signal processing, network science, and decentralized machine learning. Welcome
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with an analytical mind and capacity to structure more than one project in parallel you have the ability to communicate complex findings clearly is a merit you speak and write English fluently Merits
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optimization methods, first‑order methods, variance reduction, distributed and parallel optimization, federated learning, generalization/robustness and privacy aspects in scalable learning algorithms. Large
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fatigue under cyclic loading in pressurized high-temperature water environments, with links to microstructure and manufacturing processes. The work combines material modeling using crystal plasticity and
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on modelling nucleation and evolution of damage under monotonically increasing or static loading in pressurized high-temperature water environments, with links to microstructure and manufacturing processes
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and supportive Laboratory of Organic Electronics (https://www.liu.se/loe ). LOE currently has >150 researchers and research students across thirteen group sharing an open lab environment for fruitful
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research within the department, and how they stand to contribute to its future development. Desirable qualifications: It is desirable to have experience with electrode binders, electrode processing and other
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(https://ki.se/en/mbb/research-division-of-medical-systems-bioengineering ) at the department of Medical Biochemistry and Biophysics. In our group we are interested in shedding light on central molecular
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of formulating them, 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