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Field
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deep learning models using the Oak Ridge Leadership Computing Facility (OLCF) systems. Conduct research with scalable transformer-based foundation models with large volumes of spatiotemporal physical
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developing new ones, including machine and deep learning methods. There will be opportunities for development of new cell line and animal models and testing, evaluation, and analysis of new genomic
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at the atomic scale, using density functional theory-accurate machine-learned potentials and molecular dynamics simulations, in close collaboration with leading European research institutes and steel industry
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or deep learning reconstructions). Knowledge of radial data acquisition strategies, artifact mitigation methods, and their use in parametric imaging (e.g., T1/T2/T2* mapping). Preferred Qualifications
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of ways. CURA’s work ranges from community engaged research to leadership development. Our varied programs seek to develop deep partnerships with community collaborators and acknowledge the expertise
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conferences (e.g., NeurIPS, ICML, ACL, EMNLP, etc.). Proficiency in programming languages such as Python, and experience with deep learning frameworks like TensorFlow, PyTorch, or JAX. In-depth understanding
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their valuable contributions and deep connection to country and pay respect to Elders past and present. Advance internationally recognised Antarctic climate and palaeoclimate research Be part of nationally funded
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(e.g. use of OpenRouter, vLLM). Experience training LLMs and deep learning in general is a plus; good communication skills in oral and written English. Contributions to OpenML or other dissemination
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. in Computer Science or a closely related field, with research focus in Reinforcement Learning, Machine Learning, Embodied AI, or AI for Education. Strong background in deep reinforcement learning, with
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with deep learning to design van der Waals heterostructures with optimised spin-orbit torque (SOT) efficiency for ultra-low-power memory and computing. Its two pillars are AUTOMATA, an automatic material