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), clinical trials, disease surveillance, and the use of novel methods including Bayesian network, machine learning, social network analysis and dynamic data visualisation tools. Further information is
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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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institute that has developed an innovative collaboration research model, which seeks to create knowledge and influence thinking so that people can lead healthier lives. ISCRR conducts and facilitates research
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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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presents an exceptional opportunity for a suitably qualified and motivated individual to engage in applied research at the intersection of artificial intelligence , process monitoring , machine learning
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record of publications in top-tier venues such as SIGMOD, VLDB, ICML, NeurIPS, ICLR, or TPAMI. You may also: Have a strong background in machine learning, particularly foundation models for spatial data
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(PhD entry Level - $108,156 p.a.) Join a collaborative and cutting-edge research environment working with world-class researchers. Apply statistics, bioinformatics, and machine learning methods
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You Completion (level A and B) or near completion (level A) of a PhD in the field of Information Retrieval, Natural Language Processing, or Machine Learning on Textual Data. Demonstrated expert