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Australian National University | Canberra, Australian Capital Territory | Australia | about 1 month ago
at ANU. We are a transformative centre for research in artificial intelligence and machine learning, computer systems and software, and theoretical foundations of computing. We span traditional and modern
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 1 month ago
at ANU. We are a transformative centre for research in artificial intelligence and machine learning, computer systems and software, and theoretical foundations of computing. We span traditional and modern
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. Desirable: Proficiency in scientific programming (e.g. Python) and familiarity with data science and machine learning techniques. Experience with geochemical analytical techniques and working in a laboratory
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intelligence (AI), machine learning (ML) and vision, natural language understanding, and robotics, to build autonomous systems that can perceive, plan, and respond to their environment in pursuit of high-level
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-atomic potentials using a combination of classical and machine-learning (ML) approaches (and a new hybrid method recently developed in our group). Some of the types of simulations that will be performed
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and oral communication skills, including drafting of academic papers and grants High level computer skills with software skills such as Microsoft Office, SAS, SPSS If this sounds like you, we highly
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of Chemistry is looking for a Post Doctoral Research Fellow to join in an exciting project Parameterisation of voltammetry in a machine learning environment. The project involves working with a multidisciplinary
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simulations using DFT (particularly of surface processes); kinetic Monte Carlo simulations; molecular dynamics simulations; classical and machine-learned force fields. Highly developed skills in scientific
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and standing recognised by the University/profession as appropriate for the relevant discipline area (e.g., AI/Machine Learning, Bioinformatics). A proven track record of research and scholarly
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. Experience with bioinformatics tools and libraries for genomics analysis (e.g., Seurat, Scanpy, CellRanger, Nextflow, Singularity, Docker). Expertise in machine learning techniques and deep learning frameworks