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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 10 hours ago
characteristics, drug efficacy, and safety profiles, and how these relationships can be predicted using machine learning based on drug-specific information, patient demographics, and clinical trial data. 2
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: deep learning, pattern recognition, machine learning and big data. Languages: English, at B2 level or above Selection process Required documentation: Copy of national identity document/passport Copy of
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Doctoral Researcher in Probabilistic Machine Learning Aalto University is a community of bold thinkers where science and art meet technology and business. We are committed to identifying and solving
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, machine learning, physical AI, and spatial AI. The RA will contribute to the development of innovative algorithms, data preparation pipelines, and experimental evaluations that are central to the
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Title: Modelling dynamics and reactivity with Machine Learning Interatomic Potentials Supervisor: Professor Fernanda Duarte Start date: 1 st October 2027 Applications are invited for a fully funded
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, including model-based, observer-based, and machine-learning approaches - Identifying markers of intelligent, intentional, and malicious manipulations of detection systems - Developing detection and
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background in mathematics, computer science, or machine learning. The work has a strong focus on developing new objectives or new architectures for medical deep learning and on new ways to measure what
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Mathjobs.org | 30 days ago
families of algorithms for cryo-electron microscopy (cryo-EM) and broader applications in data science * Protein structure prediction: Combining traditional and machine learning approaches to protein
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families of algorithms for cryo-electron microscopy (cryo-EM) and broader applications in data science * Protein structure prediction: Combining traditional and machine learning approaches to protein
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CFM-Centro de Física de Materiales/MPC-Materials Physics Center | Donostia-San Sebastian, Pais Vasco | Spain | about 2 months ago
to establish a closed-loop platform that combines computational inverse design, robotic synthesis, online characterization, and machine learning-driven optimization of plasmonic nanoparticles. Join us