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architectures (CNNs, RNNs). Experience with explainable AI (e.g., SHAP, LIME) is preferred. Quantitative Analysis: Demonstrated ability to handle multimodal datasets, conduct statistical analysis, and apply
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science, engineering, electronics, materials science, mathematics, nanoscale science, neutron science, physical science, physics, and statistics. This collection of information is needed to facilitate the administrative
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science, engineering, electronics, materials science, mathematics, nanoscale science, neutron science, physical science, physics, and statistics. This collection of information is needed to facilitate administrative
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use the algorithms in practice, when little to no assumptions can be made on the data. Required Qualifications PhD in computer science, mathematics, statistics, or related fields (by the start date
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The post holder will be responsible for leading on the data analyses in A-STAR as well as data management, supported by a Research Associate in statistics and several data managers. The post holder will be
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to measure nutrient availability, soil microbial activity, and plant responses. Data management and analysis: Collect, manage, and analyze experimental data using statistical and modeling tools. Interpret
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, Medicare and/or commercial claims data, a deep understanding of analytical methods and statistics, and advanced programming skills are therefore desired. The role will also involve preparation of graphical
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. or M.D./Ph.D. in areas such as Data Science, Statistics, Computer Science, Epidemiology, Environmental Health, or a related field. Demonstrated expertise in large scale analysis and familiarity with health
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will hold demonstrated experience in epidemiological methodologies and data analytics. Your skills will include critical appraisal of epidemiological evidence, and statistical analysis to evaluate large
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Primary Lymphoedema utilising a range of computational and statistical approaches. We are seeking a candidate with a background in computational biology and experience in the analysis of genetic data