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REQUIREMENTS The Tomato Genetics and Breeding Program in the Department of Plant Science at Penn State University is seeking a part-time researcher to assist with field-based tomato breeding and cultivation
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About the role We are seeking a talented Postdoctoral Researcher with expertise in healthcare AI to join the Modernising Medical Microbiology (MMM) Unit at the University of Oxford. This is an exciting opportunity to lead innovative research at the interface of AI and clinical medicine, working...
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University of Strathclyde will lead the wind energy training and research elements of the programme. Funded by ESB and EPSRC, this 4 year this PhD studentship, at the University of Strathclyde is in the area
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Fully Funded PhD Research Studentship tax-free stipend of £20,870 Design, Informatics and Business Fully Funded PhD Research Studentship Project Title: Profiling hardware and feasibility of new
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October 2026 start ONLY For January and April starts please use the relevant application. This form is only to be used by those self-funded applicants seeking a place on a research degree programme at
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on conventional computing platforms such as GPUs, CPUs and TPUs. As language models become essential tools in society, there is a critical need to optimize their inference for edge and embedded systems
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to apply, please use the below Programme Application Portal to get in touch with the Programme Admission Admin. Application received in other channels will be re-directed and requires apply for a second time
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emerging photonic microdevices promising to revolutionise computer, communication, and sensing technologies must be performed with unprecedented picometre (one-hundredth of the atomic size) precision
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This self-funded PhD opportunity explores assured multi-sensor localisation in 6G terrestrial and non-terrestrial networks (TN–NTN), combining GNSS positioning, inertial systems, and vision-based sensors to deliver resilient, high-accuracy positioning. The project sits at the intersection of...
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members of staff. Research in the Department is organised into six themes : Causality; Computational Statistics and Machine Learning; Economics, Finance and Business; Environmental Statistics; Probability