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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
Position Title Post-Doc Research Associate Vacancy ID PDS004802 Full-time/Part-time Full-Time Temporary Hours per week 40 FTE 1 Work Location Chapel Hill, NC Position Location North Carolina, US Hiring Range
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Project Title: Use of AI and Machine Learning to Accelerate Formulation and Delivery of Medicines Post Duration: 12 Months, Full-Time Post Salary: €46,306 - €52,863 (IUA PD1 Salary Scale) For an information
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these autonomy and self-adaptation capabilities. Three major challenges have been identified: (P1) modelling uncertain environments where robust, weakly supervised machine learning algorithms can be deployed
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Max Planck Institute for Demographic Research (MPIDR) | Rostock, Mecklenburg Vorpommern | Germany | about 8 hours ago
qualified Post-Docs interested in Computational Social Science. This application call is targeted to the broad topic of artificial intelligence, computing, and society. Research Themes and Teams The Network
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. Responsibilities may include: Designing and conducting studies on the clinical impact of GLP-1 and other metabolic therapies Developing and applying computer vision and machine learning techniques to analyze
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Modeling. Machine Learning Interatomic Potential (MLIP) accelerated simulations. Demonstrated ability of coding in Fortran, Shell, or Python with development experiences. Deep knowledge in excited states and
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Join and help us to derive global forest biomass data from the European Space Agency’s Biomass satellite mission. If you have interests in remote sensing, machine learning and forests, this is the
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), Kinetic Modeling. Machine Learning Interatomic Potential (MLIP) accelerated simulations. Demonstrated ability of coding in Fortran, Shell, or Python with development experiences. Deep knowledge in excited
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Professor Max Frenzel is currently recruiting for a 2-year Post-doc position (extendable) to join the new Mineral Exploration and Exploitation Group at KAUST. The focus of the position will be
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technologies generate unprecedented volumes of molecular data at cellular resolution, opening new avenues for the application of machine learning to fundamental biological problems. The postdoctoral researchers