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, pharmacology, genomics and multi-omics, as well as growing methods in advanced analytics of health data e.g. machine learning to improve human health with a focus on therapeutics. These posts will work alongside
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and industrial project partners. You will be responsible for: Developing and adapting machine-learning approaches for structure-based and generative molecular design. Integrating physicochemical
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. Postdoctoral Associate Department of Neurosurgery | Duke University School of Medicine Be You. The Department of Neurosurgery at Duke University School of Medicine is seeking a Postdoctoral Associate to join a
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geoscientific process models, as demonstrated by presentations, publications and/or repositories Expertise in applying Bayesian statistical methods, machine learning methods, or related statistical inference
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. machine learning, computer science, mathematics, statistics, physics, theoretical neuroscience or a closely related field) with significant post-qualification research experience. You will experience
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and apply AI and machine learning methods for signal processing, image analysis, data fusion, and prediction; · build physics-informed and hybrid AI models that combine geophysical knowledge with data
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therapeutics and antimicrobial peptides. The Postdoctoral Researcher will apply computational modeling, structural analysis, and machine learning approaches to support mechanistic studies of cellular signaling
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assigned as needed. The ILS Lab develops innovative methods at the intersection of operations research, artificial intelligence, and machine learning to solve complex supply chain, logistics, and
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or machine learning is highly desirable Prior experience with liquid biopsy work is welcome but not required Proven ability to think creatively, work collaboratively, and communicate effectively Fluency in
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of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI implementation. Ability to apply AI to interdisciplinary research or developing AI models