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Apply now Job no:502129 Work type:Full time Location:Launceston Categories:Balanced Research/Teaching Coordinate, develop and teach high-quality coursework Effectively contribute to research
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the world’s largest supercomputers (Polaris, Aurora) and some of the most advanced characterization tools in the world at Argonne and Sandia National Labs. Candidates with a background in deep learning
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highly stimulating environment that engages the best and brightest faculty and students to conduct deep and impactful research. Our faculty's research expertise and strengths cover several key
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curiosity and a deep sense of responsibility, they provide invaluable contributions to research and teaching, thus enriching our society. Are you also inspired and driven by the desire to make a meaningful
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materials. Where to apply Website https://www.academictransfer.com/en/jobs/357941/phd-position-in-explainable-ai-… Requirements Specific Requirements We are looking for a collaborative and aspirational new
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Gorlitz, Sachsen | Germany | 2 months ago
programming skills in languages such as Python, C/C++ and CUDA # Familiarity with modern deep learning frameworks like Tensorflow 2.x.x, PyTorch # Mandatory experience with High-Performance Computing (HPC
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excellence, and advances a supportive learning environment for residents and fellows. This recruitment comes at a pivotal time of strategic growth and investment across the MU Health enterprise. University
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, communication, behavioral, analytical, technical and research skills. They learn evidence-driven strategies for identifying and segmenting markets, reaching and engaging potential consumers, and converting them
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in at least one major programming language, such as Python, is expected Familiarity with deep learning frameworks and modern NLP toolkits is an advantage Motivation to publish research results in
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of published research relevant to clinical medicine, especially those using quantitative research methodologies. Experience and demonstrated achievement in University-level teaching and learning. A record of