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Field
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field (e.g., engineering, applied mathematics, statistics) Strong theoretical understanding and practical experience in machine learning, multimodal foundation models, continuous learning, and agentic AI
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) Mathematics and Statistics (10 ) Other Non-Science & Engineering (13 ) Physics (16 ) Science & Engineering-related (1 ) Social and Behavioral Sciences (29 ) Age: Must be 18 years of age Veteran Status
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venuesStrong programming skillsSolid mathematical foundation, including linear algebra, probability, statistics, and optimizationBroad and in-depth experience with machine learning algorithms and deep learning
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Job Description The section for statistics and data analysis is looking for a Postdoc to join the section, with the aim of strengthening the section’s work within scientific consultancy in
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to: Develop mechanistic and data-driven models to analyse concentration–response relationships and biological readouts from advanced in vitro assays Apply statistical and computational methods to quantify
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molecular tools, capsid architectural modeling, classical nucleation theory, molecular dynamics simulations, and protein expression. The ideal candidate will have a background in mathematical biology
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scholarly sector. AI3 includes more than 70 faculty members with interests ranging from novel algorithms, architectures, and mathematical / ethical foundations to applications in art, biological sciences
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mathematics/statistics/computer science, willing to specialize their research on large language models (LLMs). The successful candidate will contribute to the development of trustworthy LLMs by focusing
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to contribute to innovative, policy-relevant research at the intersection of statistics, infectious diseases epidemiology, and global health. Appointment Details The successful applicant will be registered
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in instrumentation and fundamentals of mass spectrometry, as well as skills in data analysis, statistics, and/or visualization is an advantage. Our offer a position for one year, with the possibility