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algorithms for microscopy image analysis problems (primarily 2D timelapse data), which are driven by real applications in life science research Develop solutions to integrate large foundation models
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the evaluation of converter and drive architectures for edge-resident intelligence; the development of advanced modulation, estimation and control algorithms for high-performance operation; and the integration
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, evaluate and describe novel algorithms for learning concepts with theoretical guarantees from unstructured data; present research results at international conferences, workshops, and journals; pursue and
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, manuscript preparation, meeting with collaborators, etc. In particular, the Research Scientist hired for this position is expected to develop AI algorithms for the directed evolution of proteins with a
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National Aeronautics and Space Administration (NASA) | Hampton, Virginia | United States | 2 months ago
questions in Earth System science is also a goal of this opportunity. Efforts are expected to be conducted in collaboration with the SAGE algorithm/data processing and validation teams, as
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at: https://www.umu.se/en/department-of-computing-science/ Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data driven models
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applicant will work with the ReXIl team, AIML, and 4DMedical to turn data into clinical impact. They will be responsible for developing algorithms for image analysis, creating predictive models for disease
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contribute to the development of fundamental aspects of computer science (models, languages, methodologies, algorithms) and to address conceptual, technological, and societal challenges. The LIG 22 research
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algorithms, computational complexity theory, and information theory Relevant coursework and experience in spiking neural networks, and statistics A strong electronics background, including experience in
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particular focus on applications relevant to the Arab world. The successful applicant will join a multidisciplinary research team working at the intersection of machine learning, algorithmic fairness, human