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Field
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systems, FPGA/RTL, and RF technologies, and CUDA coding for GPU acceleration is a plus. Strong leadership, communication, and documentation skills.
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research. BOLD also has access to national compute resources (3M GPU hours on Isambard for the first 1.5 years) and we are working hard to get to 5000 H100 equivalent compute capacity in total across
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, or be awaiting their viva. Ideally, you will have experience with the numerical analysis and computational approximation of PDEs using the finite element method. Experience with degenerate parabolic
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on improving perinatal bereavement care for Aboriginal families who have experienced pregnancy or early life loss. Working under the direction of the Lead Chief Investigator, you will lead a key component of
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education and training of Pharm.D. graduates. A key element of the program’s success is preparing Fellows to meet evolving workforce needs across various sectors of the pharmaceutical industry. Fellows have
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experiences on computer vision • Strong programming skills in using Deep Learning tools like PyTorch and GPU clusters. • Good written and verbal communications. • Open to Fixed Term Contract
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and performance prediction; Finite-element electromagnetic analysis; and Machine topology development, design methods and optimisation. Your experience does not need to be in a particular machine
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Processing Unit (GPU) hardware. Working Conditions Needs to be able to successfully perform all required duties. Office/research environment; some travel and weekend work is required. UTRGV is a distributed
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We are looking for a researcher, whose expertise lies in computational fluid mechanics and finite element methods, to work with Matthew Hubbard and Reuben O’Dea on a Wellcome Trust funded project
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of environmental factors of 60,000 subjects across multiple time points. Our research laboratory has great computing capacity, including multiple H100 and A100 GPU systems for deep learning, and computing clusters