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meet the CLIA/CAP Education Requirements established to perform high-complexity testing. Minimum educational or experience requirements may be modified on a case-by-case basis at the discretion
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modeling and networked biological systems. You will work at the intersection of high-performance computing (HPC), computational biophysics, and machine learning, leveraging leadership-class computing
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coordination with program staff and report equipment repair or replacement needs in a timely manner. Required Skills High school diploma or equivalent required. Minimum of five (5) years of professional HVAC
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Engineering Candidates must have a PhD in computer science or closely related disciplines, together with an international reputation in research and scholarship. An established track record in high quality
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Dalhousie University | Halifax Mid Harbour Nova Scotia Provincial Government, Nova Scotia | Canada | about 18 hours ago
for sustaining research excellence, fostering collaboration, and maximizing the impact of institutional investments. Dalhousie’s CORES program plays a critical role in ensuring that sophisticated, often high-cost
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selection cycle and operating the year-round program; set goals and expectations, provide regular feedback, and support staff development in a collaborative, inclusive, and high-performing team culture
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in research using state-of-the-art facilities. • Advanced High Performance Computing Cluster: Run advanced simulations and analyze them using numerical tools. • Global Exposure: Contribute
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maintaining Mason?s commitment to high?impact research, national security partnerships, and efficient contract performance. Responsibilities: Program Leadership and Execution Leads the planning, execution, and
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develop software for high-energy particle physics. Optimize software for performance, scalability, and efficiency on modern computing architectures, including HPC and distributed systems. Participate in
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on the cloud or high-performance computing (HPC) systems that can store, search, analyze and annotate data of the volume and complexity of the Rubin Observatory’s Legacy Survey of Space and Time (LSST) data