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through data-driven modeling and optimization. The successful candidate will work at the intersection of thermal-fluid sciences, control theory, and artificial intelligence/machine learning to advance
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at the intersection of advanced microscopy, atom probe tomography (APT), artificial intelligence and materials science. Working with world-class characterisation facilities, they will develop quantitative and AI
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group at the frontier of autonomous science across two projects. The primary assignment for the first 9 months is A-WILD (AI-driven Workflows for Intelligent Lab Discovery), a DOE Genesis Mission project
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network optimization for 6G/FutureG wireless networks especially on the Internet of Intelligent Things under the supervision of Dr. Lingjia Liu (https://lingjialiu.ece.vt.edu). Successful candidates will
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Materials A single PDF or Word document containing a resume, letter of interest, and a list of the names and contact information for three (3) professional references is required to apply. Important
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will contribute to and lead research in the following areas related to our current and past projects https://gxrlab.rf.gd/research/ : Intelligent Motor Skill Learning: Developing AI-driven, physics
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, research and practice across five core domains: Asset & Maintenance engineering, Intelligent Manufacturing Systems, Personalised Health Technology, Resilience Engineering, and Sustainable Production, Energy
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“drylab” techniques. Current drylab approaches focus on bioinformatics, including emerging artificial intelligence models. Current wetlab approaches focus on RNA and chromatin biology. Candidates should
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October 2026 Apply now Do you want to use artificial intelligence, geospatial data science, and urban analytics to create healthier and more equitable cities? Are you excited about developing innovative AI
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into concrete solutions for the challenges of today and tomorrow. These challenges are changing rapidly. That is why we focus on themes such as energy, climate, digitalisation, artificial intelligence (AI), and