37 algorithm-development-"the"-"University-of-Michigan---Flint" Fellowship positions in United Kingdom
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. This role will contribute the development of novel machine learning algorithms for wireless sensing and communication and the proof of concepts for next-generation wireless communication, collaborating with
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, this role will contribute the development of networks coordinated sensing and communication solutions and the proof of concepts for next-generation wireless communication, collaborating with other team
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. Allied to other programmes in Singapore and the UK, it represents a unique opportunity to be at the forefront of research and development into securing the vital information that flows from implantable
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. Allied to other programmes in Singapore and the UK, it represents a unique opportunity to be at the forefront of research and development into securing the vital information that flows from implantable
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work with hands-on offloading algorithm design and development for IoT networks. The core responsibility is to build and validate edge-assisted offloading strategies, complete with software APIs, through
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into: Developing and implementing Quantum Dynamics algorithms for non-adiabatic. Studying the photo-activated non-adiabatic photochemistry of prototypical chromophores. Simulating measurable signals from time
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Health. This role offers the opportunity to build on our extensive track record and ongoing work in developing AI solutions for healthcare, while contributing to the next generation of predictive tools
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relevant research techniques and methodologies Strong publication record commensurate with the applicant’s career stage. Algorithmic and model development skills, and a familiarity with relevant machine
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. Research experience in relevant research techniques and methodologies 3. Strong publication record commensurate with the applicant’s career stage. 4. Algorithmic and model development skills, and
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all, of these disciplines is required. Proven track record of scientific publication. Demonstrated experience in developing/adapting computational models or algorithms to analyse biological or ecology