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multiphase flow behavior. The project also involves applying machine learning and computer vision techniques to enhance data analysis, pattern recognition, modeling, and prediction. The role requires a solid
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at cell membranes; Apply machine-learning models trained on simulation data to study how lipid composition and genetic variation influence the conformational and phase properties of membrane-associated
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, respectful, and stimulating environment. We value communication and collaboration and a workplace that promotes learning and development for all employees. We are also committed to building a safe and positive
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, and the mathematical and computational foundations of neural networks. Familiarity with the following areas is meritorious: machine learning, computational complexity, tree automata and tree
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experience with advanced signal processing concepts as well as digital filters is advantageous. Your workplace You will be working at the Division of Electronics and Computer Engineering (ELDA), which conducts
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theoretical analysis, implementation of methods in computer codes, use of state-of-the-art high-performance computers in Sweden and in Europe, application of machine-learning and AI techniques, and
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, pharmacology, inflammation, cancer and neurobiology. We also teach students studying at various programs and independent courses in cell biology, physiology, neurobiology, anatomy and histology
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northern Europe. Our research covers a broad spectrum of fields, from core to applied computer sciences. Its vast scope also benefits our undergraduate and graduate programmes, and we now teach courses in
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well as digital filters is advantageous. Your workplace You will be working at the Division of Electronics and Computer Engineering (ELDA), which conducts teaching and research in a broad range of areas, from
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Chemistry (experimental/computational physical chemistry) -Transition metal photocatalysts studied by femtosecond X-ray science with a focus on hybrid experimental/machine-learned structural dynamic analyses