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Requirements: PhD degree in physics Demonstrated experience in computer sciences Demonstrated experience in handling large size database Knowledgeable in theoretical physics, and at minima basic knowledge in
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Language Processing (NLP) methods, with a special focus on generative Large Language Models (LLMs), to interrogate a very large sample of Electronic Health Records from people with epilepsy across multiple NHS
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testing, real-world research, and contributing to Australia's defence capabilities, we'd love to hear from you. About the Role You'll be part of a research team focused on large-scale structural testing
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large databases is required. The candidate is expected to partake in design of the epidemiological studies, statistical work (SPSS but also other programs such as R), presentations and preparation
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about experimental testing, real-world research, and contributing to Australia’s defence capabilities, we’d love to hear from you. About the Role You’ll be part of a research team focused on large-scale
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turbulence data, together with fine-scale profiles from standard Argo floats, to quantify rates of vertical and horizontal ocean mixing, and you will apply inverse methods to investigate the role
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. This role represents a unique opportunity to generate biological insights from our large-scale research datasets including single-cell multiomic sequencing data from skin and blood to enable
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Large Language Models Natural Language Processing (NLP) Deep Reinforcement Learning Theoretical Foundations of Deep Learning and AI Optimization Techniques in Machine Learning Collaboration and Mentorship
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Fellow will be using Natural Language Processing (NLP) methods, with a special focus on generative Large Language Models (LLMs), to interrogate a very large sample of Electronic Health Records from people
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the SG100K team to shortlist participants for recruitment Run focus groups to get user feedback on procedures and concerns Check data flows, analyze the data to inform future large-scale implementation Write