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operational data and machine learning. You will be based at UCL mechanical Engineering, and collaborate with industry and port partners on system design, prototyping, and lab-based trials. Key responsibilities
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achievements in the field of physical sciences documented by publications in renowned journals 2. Additional Requirements: 1) statistical analysis of large data sets 2) knowledge of machine learning 3
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University of Massachusetts Medical School | Worcester, Massachusetts | United States | about 1 month ago
immune modulation using CAR Tregs. Designs and executes experiments to evaluate the safety and efficacy of genome-edited cells. Assesses the functionality of engineered cells,and evaluates
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, genetic information, national origin, race, religion, sex (including pregnancy and pregnancy related conditions), sexual orientation or military status. Duke aspires to create a community built on
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control subjects based on diffusion MRI images and functional MRI responses. Duties include: Developing machine-learning and/or deep learning pipelines for classifying patients of optic neuropathies and
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/Computer/Mechanical/Materials/Nuclear Engineering or related discipline. • Excellent foundation in materials processing • Hands-on experience with device and system characterization. • Experience in
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disciplines strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation and the ability to work independently with
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to these challenges, working with high performance and distributed computing environments, working with large-scale machine learning models, and a proven research record of scholarly contributions through publications
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strong research capabilities with a deep understanding of trading to design, validate, backtest, and implement statistical and advanced machine learning models. Your work will span a range of initiatives
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) platforms used in machine learning, big data and artificial intelligence (AI) based applications (CPUs, GPUs, AI accelerators etc.) require high power demands with optimized power distribution networks (PDNs