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Apply now Job no:501817 College / VP Area: College of Engineering Work type:Staff Location:Newark, DE Categories:Research & Laboratory, Full Time Context of Job: As a Post-Doctoral Researcher, you will support Prof. Yuping Zeng with the frontier of analog circuit design, implementation and...
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Duration: 1-year appointment with possibility of renewal for a 2nd year. About the Department Our research group works at the intersection of machine learning, medical imaging, biomedical engineering, and
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-UAS technologies o Multi-agent systems and swarm robotics o Autonomous navigation and guidance o Computer vision and perception o Machine learning
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single-cell and single-nucleus multi-omics, machine learning/AI, computational biology, and experimental validation to understand cardiovascular disease progression and identify novel therapeutic targets
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/DPhil in robotics, computer science, machine learning, informatics, AI, or a closely related field. You will have an excellent academic track record in topics relevant to locomotion and manipulation; path
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, combining experimental photonics with numerical modelling and modern machine-learning and optimisation techniques. The research will include coherent beam combination, programmable beam shaping, optical
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biologists and other researchers. You will be responsible for applying computational chemistry, chemoinformatics and machine learning approaches to drug discovery, including molecular modelling, virtual
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lab experiments Publish results in top-tier journals in related fields Assist in mentoring PhD students Job Requirements: PhD degree in mathematics, systems engineering, or machine learning Expertise in
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The VCC center at KAUST is looking for postdoctoral researchers and research scientists in Prof. Wonka's research group. The topics of research are computer vision, computer graphics, and deep
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the supervision of the Principal Investigator, including but not limited to the following: Develop new computational tools through the application of AI / deep learning / machine learning / statistics on spatial