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computing, manifold learning, geometric data analysis, or phylogenetic models of trait evolution Ability to collaborate and contribute to an interdisciplinary research environment. Scientific originality
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, physical and chemical characterization, use of LSRI facilities, and in vitro evaluation. The project is a collaboration between KTH, RISE, Larodan, and Karolinska Institutet. The position will be shared
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of complex brain processes. The prospective PhD candidate collects brain MSI data and develops novel machine learning methods in connection to generative models such as flow matching. Therefore, the doctoral
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, 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 focuses
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are seeking a candidate who is detail-oriented, quick to learn new skills, and able to work both independently and collaboratively. In addition to the qualification requirements listed above, we highly value
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-specific immunotherapy. The research group conducts experimental and translational research in close collaboration with specialists at Skåne University Hospital. The team collects samples of allergic
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visualization and scientific communication Extensive knowledge of relevant machine learning and AI techniques Exceptional collaborative abilities Self-motivated individual with ability to work independently
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and conditions for Open Science and FAIR, as well as the application of these. Documented experience of leading collaborative projects. Skills in coordination and communication, and the ability
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++ or similar) and an interest in quantitative or computational approaches are required. Prior experience with image analysis, machine learning, signal processing, or structural biology is meritorious but not
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collaborate closely with research groups to ensure our solutions are stable, user-friendly, and future-proof. You will join a growing team with skilled system developers. In this role, you will: Develop and