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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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of almost 11,000 individuals, including approximately 7,700 academic staff members, who passionately pursue answers to the profound questions that shape our future. Fuelled by curiosity and a deep
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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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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
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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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(see http://orcid.org/ ) Teaching portfolio including documentation of teaching experience Academic Diplomas (MSc/PhD) You can learn more about the recruitment process here . Applications received after
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of receiving their PhD. In particular for this position, the following is required: PhD in data science, AI, computer science, machine learning, Earth system science, climate etc., with a thesis subject relevant
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Your Job: We are looking for a PhD student to contribute to the development of fast, accurate, and physics-informed machine learning models for predicting blood flow in patient-specific vascular
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and engineers. Key Responsibilities 1. AI Model Development & Testing Assist in developing machine learning and deep learning models for medical imaging analysis. Implement and fine-tune models using
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, 3-D dosimetry, oncologic and biological imaging, automatic treatment planning, radiomics and deep-learning, modeling of radiation damage for normal tissues and of tumor control using radiation