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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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research areas, preferably demonstrated by publications in high-impact venues. Experience with machine learning frameworks (e.g., PyTorch, JAX) and / or computational materials methods is essential
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What You’ll Need: PhD in computer science, artificial intelligence, machine learning, computational biology, biomedical engineering, or a closely related quantitative field. Strong foundation in modern
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. Expertise in artificial intelligence and machine learning. Recent research experience in the development of first-principle wave models. Recent research experience in the development of numerical codes
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into commercial products that solve big problems. We support research that universities, companies, and venture capital firms don’t fund because they view it as too risky. We prefer to use the word “challenging
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the Section for Catalysis and Organic Chemistry at the Department of Chemistry. The group has extensive experience in computational modelling, reaction mechanisms, and machine learning for catalyst design and
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holder must have: Expertise in advanced theoretical and computational electromagnetics, including high frequency asymptotics. Expertise in artificial intelligence and machine learning. Recent research
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knowledge within advanced modelling/analysis methodology Applicants must have hands-on experience working with model lipid membranes Applicants must be proficient with computer programing Fluent oral and
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Computer Science, AI/ML, Computational Biology, Food Science with computational expertise, or a related field. Experience with natural language processing, machine learning frameworks (e.g., PyTorch
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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