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will have: A PhD* or equivalent qualification / experience in Electrical/Electronic Engineering, Signal Processing, or a closely related field. Proven experience in radar systems, radar signal processing
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engineering or a related discipline. Strong analytical, problem-solving, communication, and teamworking skills, along with experience in computational modelling are essential for the role. What we offer: - A
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Applications are invited for the prestigious Eric and Wendy Schmidt AI in Science Fellowships, a program of Schmidt Sciences, commencing 1 September 2026. This 1-year appointment at Imperial College
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. Computational modelling approaches are frequently used alongside experimental research programmes and much of our research crosses traditional boundaries, including the relationship of biodiversity to the health
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, automotive, electrical/electronic engineering or computer science. Also, experience in the following areas is highly desirable: Control development and implementation, including neural networks Instrumentation
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, automotive, electrical/electronic engineering or computer science. Also, experience in the following areas is highly desirable: Control development and implementation, including neural networks Instrumentation
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already commenced training in general cardiology and wish to gain more sub-specialty experience in Cardiac MRI (CMR), by taking an Out-Of-Programme Experience (OOPE) from their current training programmes
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Applications are invited for prestigious Eric and Wendy Schmidt AI in Science Fellowships, a program of Schmidt Sciences, commencing 1 September 2026. There are up to 8 positions available, with a
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Applications are invited for prestigious Eric and Wendy Schmidt AI in Science Fellowships, a program of Schmidt Sciences, commencing 1 September 2026. There are up to 8 positions available, with a
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computer science, electronics, and electrical engineering. Research takes place in a multidisciplinary, collaborative environment and draws on our outstanding facilities. With over 550 researchers from many