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, spectropolarimetric inversion techniques, and machine-learning–based approaches, for the physical interpretation of solar images and spectral profiles. Special consideration will be given to applicants with experience
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to an advanced Laboratory Directed Research and Development (LDRD) project, "Machine Learning Steered EXAFS Fitting for Autonomous XAS Analysis," aimed at revolutionizing real-time analysis of X-ray Absorption
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and machine learning with Prof. Jason M. Klusowski (https://klusowski.princeton.edu). The position is for one year with the possibility of reappointment based on satisfactory performance and
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digital health Computing systems and networks Cybersecurity Human-computer interaction Machine learning and artificial intelligence Software engineering Position details Positions are intended
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Job Title Postdoctoral Researcher Agency Texas A&M Engineering Department Electrical Engineering Proposed Minimum Salary Commensurate Job Location College Station, Texas Job Type Staff Job
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relevant experience in an applicable social science. Knowledge, Skills and Abilities: Comprehensive understanding of scientific theory and methods. General computer skills and ability to quickly learn and
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sciences, computer science, machine learning, and education research. Research Themes The research themes identified for the NTO postdoc include, but are not limited to, the following: Developing
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AI to predict safety outcomes for multiple targets and combination therapies Collaborate with research teams and data scientists to design data-driven strategies using machine learning/AI methods
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an uncertain future. In the context of the twin transition – that is, the complex relationship between digitisation and the green transition – the focus of this postdoctoral position is the question
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microscopy methods (darkfield, photothermal, ultrafast, interferometric), electron microscopy, machine learning and other advanced statistical methods. Required Application Materials Cover letter, curriculum