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reinforcement learning approaches for autonomous guidewire shaping and control. • Design experiments, validation strategies, and quantitative performance metrics for robotic navigation and wire-shaping systems
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Qualifications Experience with graph neural networks, machine-learning interatomic potentials, or related scientific machine-learning methods for atomistic systems. Familiarity with uncertainty quantification
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to support system-level navigation development. • Track progress toward defined project milestones and contribute to technical reports and project updates. • Prepare manuscripts, presentations, and other
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Experience with remote sensing products related to vegetation, aquatic systems, or biodiversity Familiarity with reproducible research practices, including version control, documented workflows, and
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part of our Pathways to the Professoriate Program. The purpose of the program is to help diversify the public health professoriate; to attract and retain academics scholars who are underrepresented
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part of our Pathways to the Professoriate Program. The purpose of the program is to help diversify the public health professoriate; to attract and retain academics scholars who are underrepresented