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machine learning models with a focus on computational chemistry (e.g. machine-learned force fields) Experience with mechanistic and physical organic chemistry studies of chemical and biochemical systems
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detector, construction of the outer detector system in the far detector, development of machine learning algorithms for particle reconstruction, and studies of CP violation in neutrino oscillations
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and research experience on the structural health monitoring of bridges. Applicants are expected to have experience in structural health monitoring, digital twins, AI and machine learning. A track record
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functionalisation, fabrication and characterisation of carbon materials for application in solar cells Predication and discovery of new materials for next generation solar cells driven by machine learning
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% superannuation) About You You will have a research focus in a STEM related area such as mathematics, statistics, computer/data science, combined with an interest in AI and machine learning. You will ideally have
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research focus in a STEM related area such as mathematics, statistics, computer/data science, combined with an interest in AI and machine learning. You will ideally have experience in coding language such as
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contribute to the AI Reliability project, focusing on improving the robustness and performance of machine learning models in real-world deployments. In collaboration with the Defence Science and Technology
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Research Fellow to contribute to the AI Reliability project, focusing on improving the robustness and performance of machine learning models in real-world deployments. In collaboration with the Defence
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to epidemiology, biostatistics and modelling including machine learning methods A sound understanding of clinical trials in mental health, including developing, evaluating or translating novel interventions. A
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: Competitive track record with demonstrated high-quality publications. Research experience related to network data mining or recommendation models. Programming skills in deep learning or machine learning