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Field
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, Statistics, Electrical Engineering, Computer Science, or a related field. Key Criteria Demonstrated experience with mathematical modelling, algorithm design, or theoretical analysis of learning systems
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would assist with you undertaking the role. Qualifications PhD, or equivalent professional experience, in Machine Learning, Statistics, Electrical Engineering, Computer Science, or a related field. Key
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institutes working at the interface of technology and life sciences. This is a unique opportunity to contribute to a research programme that is technique-agnostic, impact-driven, and unafraid to push
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aims to achieve reliable genome design and synthesis – engineering cells to have specific functions – which will be a major milestone in modern biology. A dedicated social science program will support
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and optimisation but not limited to data driven monitoring for control and operation. You must have a good master’s degree in electrical engineering, with Power and Control Engineering major
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outcomes into implementation pathways, pilot studies and feasibility assessments What You’ll Need to Thrive You will be successful in this role if you bring: A PhD in Electrical Engineering, Mechanical
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College of Chemistry and Molecular Engineering, Peking University | Exeter, England | United Kingdom | about 4 hours ago
to the overall architecture of the project’s wireless neuromodulation system. About You You will have: A PhD (or equivalent) in Electrical Engineering, Electronics, Electromagnetics, Bioelectronics, or a related
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This 36-month postdoctoral position is part of the project ENLIGHT (Enabling a Lifecycle Approach to Graphite for Advanced Modular Reactors) consortium, a £13.2 million, five-year programme
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nanoelectronics, microelectronics, semiconductor devices and VLSI technology. You should hold or be nearing completion of a PhD and have strong ability in either electrical and electronic engineering, physics
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findings, and help attract funding. PhD in Computer Science, Computational Bioengineering, Mechanical or Electrical Engineering Excellent coding skills Preferably a familiarity with machine learning and deep