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to measure these backgrounds in data. The project also aims to explore to which extent machine learning methods can help with these tasks, e.g. object reconstruction and signal vs background discrimination
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of studies indicate a clear connection between oral health and general health, and there is a great need to develop this research area. Despite this, knowledge and communication between odontology and medicine
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to which extent machine learning methods can help with these tasks, e.g. object reconstruction and signal vs background discrimination. This will become more of a focus later in the project. Beyond
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colleagues within and across disciplinary boundaries, efficient decision-making processes and a vibrant research environment involving senior researchers, doctoral students and lecturers. The department offers
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close collaboration among colleagues within and across disciplinary boundaries, efficient decision-making processes and a vibrant research environment involving senior researchers, doctoral students and
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-based positioning and sensing, and associated signal processing algorithms. Work duties Employment as an assistant professor is a tenure track position, which aims for the holder to develop
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responsibilities Financial coordination of projects within SciLifeLab in collaboration with multiple universities. Manage budgets, fund allocations, and payment flows Serve as financial contact point for project
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of stimulation, how this affects behavior and signaling in neuronal circuits. By comparing spatially selective signaling, for example through optogenetics, with the clinical treatment method DBS, the goal is to
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, including a joint postdoctoral programme of the Nordic EMBL Partnership for Molecular Medicine, drive fund raising and manage external reviews and refunding process. You will use your scientific and
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manufacturing processes. The department also runs a business research school, EXACT. It aims to contribute to a sustainable manufacturing industry as well as future-proofing Swedish process-manufacturing industry