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Field
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limited to: “Data Analytics for Social Research”, “Applied Analytical Statistics for Social Scientists”, “Machine Learning with Social Data” and “Social Networks Analysis”. The appointee should be prepared
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, and openly release evaluation code. What is Required: A recent Ph.D. (within the last 1-2 years) in Computational Biology, Bioinformatics, Machine Learning, Computer Science, Statistics, or a related
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Australasia. More than 9,000 students study across our ten schools and departments, learning from internationally recognised educators and researchers. Our staff and students can connect with our flagship
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research infrastructure. Apply advanced statistical, machine learning and data engineering methodologies to large-scale, longitudinal datasets, contributing to innovative melanoma and skin cancer research
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. Ideal candidates will have demonstrably strong research skills, evidenced by multiple publications in top-tier machine learning or artificial intelligence conferences and/or leading scientific journals
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will be a part of data collection, analysis, modeling and simulation for this project. Learning Objectives: Under the guidance of a mentor, you will have the opportunity to learn about drug development
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to): biophysics, cold atom physics, electronic structure theory, hydrodynamics, machine learning, materials science, statistical physics, strongly correlated electrons, and quantum information. Theorists who wish
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Data Analytics, including but not limited to: “Data Analytics for Social Research”, “Applied Analytical Statistics for Social Scientists”, “Machine Learning with Social Data” and “Social Networks
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, hydrodynamics, machine learning, materials science, statistical physics, strongly correlated electrons, and quantum information. Theorists who wish to be considered for sponsorship as a Klarman Fellowship
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a wide range of disciplines and professional backgrounds—including government, journalism, diplomacy, civil society, and academia. The Postdoctoral Fellow may be invited to teach a Harvard class