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an outstanding environment in which to develop machine learning tools and engage with an interdisciplinary community of researchers with an interest in AI for healthcare. The post holder will have opportunities
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Details Posted: Unknown Location: Salary: Summary: Summary here. Details Posted: 01-Aug-26 Location: St. Louis, Missouri Type: Full-time Categories: Academic/Faculty Other - Academic/Faculty
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statistical and machine learning, deep learning, chemometrics, multimodal data fusion, computer vision, uncertainty-aware modeling, stochastic control, optimization, and deployable edge-to-cloud decision
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data analysis, causal inference and predictive modeling using machine learning methods. St. Jude leads two of the world's largest pediatric survivorship research studies, St. Jude Lifetime Cohort Study
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of algorithms, machine learning, optimization, scientific software development and high-performance computing. The division is also an important part of the eSSENCE strategic collaboration on e-science and of
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of electrochemistry and artificial intelligence. Ideal candidates will have experience in machine learning, large language models, AI-agent development and computational workflows, with particular interest in building
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, and machine learning within the scope of ACAG. The postdoc will have various opportunities for professional development, including contributing to and leading grant proposal development (e.g., external
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machine learning for the next generation of AI models – uncertainty-aware foundation models, generative models and world models – with the support of competent and friendly colleagues in an international
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-VIS-NIR). Experience in hyperspectral data processing (HMSPL, μXRF, μXAS) and statistical analysis (clustering, machine learning) is preferred. Familiarity with fossilization processes and taphonomic
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-cell or spatial transcriptomic analysis is desirable. Experience with machine learning, LLMs, AI agents, multimodal data integration, or automated biological interpretation workflows is desirable but not