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Field
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departments to advance Duke’s Climate Commitment. The program emphasizes faculty-mentored research, teaching innovation, and public engagement, providing Fellows with resources and networks to launch impactful
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Biology with both high-throughput experimental (proteomics and genomics) and integrative computational (network analysis and machine learning) methodologies, aiming to understand gene functions and their
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developing a new quantum sensing platform for probing correlated phases of matter at the atomic scale. The postdoctoral researcher will lead the theory component of a research program, developing microscopic
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Postdoctoral Researcher – AI-Augmented Decision Science Indiana University Bloomington Department of Psychological & Brain Sciences and Luddy School of Informatics, Computing, & Engineering Position Overview
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Biology: Strong background in systems biology and regulatory network modeling Interdisciplinary Collaboration: Experience working across disciplines with computational biologists, computer scientists, and
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and great opportunity of interdisciplinary training in machine learning and functional genomics. The project combines cutting-edge computational approaches, especially state-of-the-art machine learning
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program is your gateway to an exciting, transformative opportunity. PRISM is designed for graduate students from all fields who want to explore world-class postdoctoral training at Stanford University
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theory concepts with new empirically derived models and new data science ideas. About NYUAD: New York University has established itself as a Global Network University, a multi-site, organically connected
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their efforts on the education of students and the performance of life-changing research across a wide range of disciplines including medicine, engineering, physical sciences, energy, computer science, and social
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-Informed Neural Networks (PINNs) and geometric deep learning. Experience with active learning, agentic workflows, or other methods for autonomous experimentation. Familiarity with high-performance computing