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Field
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with faculty, clinicians, researchers, and trainees across colleges, departments, and research centers. Facilitate interdisciplinary projects involving Dentistry, Medicine, Engineering, Computer
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facilities around the world. Profile We are looking for a person with: PhD in physics, engineering, computer science, or a related field. Experience with inverse problems and 3D reconstruction methods
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engagement and participatory research with quantitative system modelling of our research group; experience with systems modeling and computer programming (e.g. Python); strong communication and scientific
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background in management science, operations research, computer science, applied mathematics, quantitative health policy, epidemiology, or a related field. As a formal qualification, you must hold a
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a Ph.D. in Information Systems, Computer Science, Data Science, Management Science, Industrial Engineering, Health Informatics, or a related field before starting the position. Strong experience in
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decarbonization, thermal comfort in extreme climates, indoor air quality, innovative building envelopes, and building performance & optimization. The position also offers the successful candidate the
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and conferences. To conduct this work, the successful candidate will use the world's first exascale system, Frontier, and collaborate with leading experts in machine learning, optimization, electric
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learning, optimization, scientific computing, domain sciences, and high-performance computing. The candidate will have opportunities to work with world-class computing resources, including ORNL’s
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MOCHA. This avenue may incorporate machine learning techniques and has direct applications for array optimization and AMOC transport estimation. Research Environment The position based at the
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of the larger departments with about 120 employees and conducts research and teaching mainly in electrical engineering and computer technology. We are located on LTH's campus in northern Lund. Within