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Field
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mapping, data-driven mapping, and context-based programming with traditional (i.e. sketches, surveys) and advanced computer-aided design (CAD) tools. Applicants must have experience with qualitative
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-performance computing clusters (>105,000 processors). This unique interdisciplinary environment emphasizes the integration of AI in life sciences, offering an outstanding platform for recent Ph.D. graduates
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may come from a diversity of disciplinary backgrounds, including but not limited to veterinary medicine, epidemiology, ecology, biology, computer/data science, economics and other social/behavioral
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 3 months ago
transformative centre for research in artificial intelligence and machine learning, computer systems and software, and theoretical foundations of computing. We span traditional and modern thinking, connecting
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Experience: Previous lab experience working with tissue culture. Previous lab experience working with protein expression and purification. Skills Written and verbal communication skills. Computer skills, data
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laboratory settings. A combination of field, greenhouse, laboratory, and computer-based activities. Accountabilities: The postdoctoral researcher will play a central role in advancing the research and
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. Strong planning, organisational, computer literacy, and interpersonal skills, with the ability to manage competing priorities effectively. Sponsorship / work rights for Australia You must have unrestricted
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, and Higgs) and in the HL-LHC detector upgrades for Phase2 (MTD, PPS). At LIP, we operate a Tier-2 computer center, provide resources for data analysis both locally and as a part of the CMS computing
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. The project will entail a combination of computational and experimental work, both directly and in collaboration with the PhD students, focusing on design and physio-chemical characterization of lipid membranes
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for funding agencies and stakeholders. Job Requirements: A PhD degree in Mathematics, Geophysics, Physics, Computer Sciences, or related areas. Strong background in numerical modeling and high-performance