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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 19 hours ago
limited to 5-axis milling, low speed machining dynamics, free form optics, physics informed machine learning (PIML), robotic machining, cutting tool design, hybrid manufacturing context. - Draft Conference
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of Engineering and Applied Sciences. The fellow will design and run human experiments, perform data analysis, and create computational models of learning and memory. A PhD is required. An ideal candidate will be
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to generate and publish high-impact machine learning research. Collection, curation, and maintenance of neural datasets Building lab equipment and software infrastructure for neural engineering experiments
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, and CAR-T and CAR-NK. As a successful candidate, you will: · Lead projects by designing and performing experimental procedures · Manage data, analyze, and report findings · Write
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-/chemo-genetics, in vivo calcium/voltage imaging, high-speed camera with machine learning, and behaviors. The lab will provide the training for relevant experimental techniques. Recent lab publications
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About the Opportunity Northeastern University is looking for a postdoctoral research fellow in artificial intelligence (AI) and machine learning (ML) as well as network science (NS) and optimization
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on academic record, as well as professional and extra-curricular experience. Basic Qualifications: PhD in Chemical Engineering, Electrical Engineering, Systems Engineering, Biomedical Engineering or related
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: 1) NK cell biology including NK cell development and cell signaling 2) Innate lymphoid cells (ILCs) 3) oncolytic virotherapy 4) chimeric antigen receptor (CAR) natural killer (NK), CAR macrophages
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differentiable programming and physics informed machine learning (Graph Neural Networks and Neural Operators) for solving inverse and optimization problems. Develop AI-accelerated numerical methods for identifying
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other professionals in the field through collaborations and participation in scientific communities. The Fellow will be asked to teach one public history course per year the SDSU Department of History and