185 electric-machine-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "https:" Fellowship positions
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Annual Leave (pro rata if part-time) plus Bank Holidays* & Closure Days* Generous pension scheme Cycle to Work & Electric Car Scheme Employee Assistance Programme Development opportunities Enhanced family
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, and laboratory operations. Job Requirements: PhD in Electrical Engineering, Computer Engineering, Physics, or a closely related discipline. At least three years of relevant research experience in
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museum in America. Today, it serves Yale University, the wider New Haven community, and the public as a center of teaching, learning, and scholarship. The museum is open to all, free of charge, and is
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; Internet-of-things; relevant laboratory equipment. Required Qualifications REQUIRED QUALIFICATIONS: 1. Ph.D. in computer engineering, electrical engineering, computer science, or closely related areas from
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of the Kempner Institute. A list of two to three proposed mentors from current faculty associated with the Kempner Institute or working on machine learning, artificial intelligence, or computational neurobiology
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Intelligence (AI) algorithms, including Machine Learning (ML) and Deep Learning (DL) techniques, for advanced signal analysis. The work will focus on developing methodologies for the detection, extraction
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, depending on eligibility: Generous annual leave: 35 Days Annual Leave plus Bank Holidays & Closure Days Generous pension scheme Cycle to Work & Electric Car Scheme Employee Assistance Programme Development
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, Bioconductor, tidyverse, SingleCellExperiment, or related software. Experience with Python and machine learning approaches is considered an asset. APPLICATION PROCEDURE Applicants should submit: Cover letter
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the field of architecture or related fields; Proficiency in computer-aided design, graphics and video software, as well as data processing and word processing software, amongst others; Advanced knowledge
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the possibility of extension. For more details on our research and recent publications, see the Geometric Machine Learning Group’s website: https://weber.seas.harvard.edu For questions, please email mweber