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, electrical engineering, cognitive science, applied mathematics, physics, or a related field. Strong computational background and hands-on experience building AI/ML models. Expertise in modern architectures
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sponsorship. Responsibilities: Performing high level experimental, theoretical, and numerical research and data analysis (45%) Presentation publication, and proposal preparation (30%) Mentoring PhD and MSME
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. Duties/responsibilities Performing high level theoretical, and numerical research and data analysis (55%) Presentation publication, and proposal preparation (20%) Mentoring PhD and MSME students (10
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National Laboratory's National Synchrotron Light Source II (NSLS-II) seeks a Postdoctoral Research Associate for AI-driven Structure Analysis for Biological Discoveries for an on-site position in
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and physical modelling. The goal of this position is to develop data-driven approaches to AI-based analysis of complex interaction systems and suitable hybrid architectures for this purpose
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workflows. The goal of this position is to develop data-driven approaches to AI-supported analysis for applications in ESS as part of the EU project “GenAI4Earth.” To this end, current developments in
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have: you will own the bacterial side of the project. You will work with our full infrastructure for vesicle assembly, synthesis and interaction analysis, with access to IBEC’s BSL-2 facilities, and in
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stakeholders involved in planning and decision-making. Qualifications Candidates must have a PhD in atmospheric physics, hydrology, meteorology, Earth system science, climate studies, applied mathematics
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 months ago
experience corresponding to mathematics through differential equations, a microbiology background including environmental microbiology, and experience with quantitative analysis of environmental and/or human
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
experience corresponding to mathematics through differential equations, a microbiology background including environmental microbiology, and experience with quantitative analysis of environmental and/or human