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an anticipated start date of August 1, 2027. We are particularly interested in candidates whose research is data-driven and leverages modern computational techniques, including artificial
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-based characterization techniques, requiring visualizing, analysis and interpretation of experimental data. The research results shall be published in peer-reviewed scientific journals and presented at
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. Novel Adversarial Machine Learning algorithms for structured data will be proposed. The algorithms will be further extended to graph-structured data. Applications of AML will also be investigated to
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. Novel Adversarial Machine Learning algorithms for structured data will be proposed. The algorithms will be further extended to graph-structured data. Applications of AML will also be investigated to
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Skip to main content FDA Data Science and AI Fellowship Organization U.S. Food and Drug Administration (FDA) Reference Code FDA-OC-2026-0002 How to Apply To submit your application, scroll to the
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understand their motivations, and build bespoke analysis pipelines of social media and financial data to understand the downstream consequences of the buying and selling of these services. The PhD will be
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centers. (See for instance http://www.mn.uio.no/geo/english/about/organisation/geohyd and https://www.mn.uio.no/geo/english/research/groups/remotesensing ). We are a growing, lively, friendly and
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academic year. For history of the chair, see https://harvaus.fas.harvard.edu/ Incumbents of the Chair will ordinarily hold the title of Gough Whitlam and Malcolm Fraser Visiting Professor of Australian
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quantitative methods, data analysis, or modeling is an advantage Very good command of written and spoken English with extensive vocabulary is required (at least C1 level according to the CEFR ), ideally
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analysis of data. Experience of work with plants or insects in the field or green house. Strong interest in crop protection and crop breeding. Good command of written and spoken English. Meriting