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Field
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-performance computing, machine learning models (eg. LLM), probabilistic models for data, novel techniques for making measurements, visualization tools, and community-oriented foundational software tools. Please
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-FATES model using: Snow cover Flux tower data The idea is to combine established iterative ensemble Kalman methods with novel emerging machine-learning-enabled model calibration techniques recently
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subsidy for research costs. Information on sponsorship during the research stay Information on sponsorship for alumni abroad Postdocs Benefit from research sponsorship in Germany at the beginning of your
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understanding of adaptive immune receptor (antibody and T-cell receptor) specificity using high-throughput experimental and computational immunology combined with machine learning. The long-term aim is to
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, computer scientists, and policy experts. The postdocs will work with Prof. Daniel Loveless on various areas of research, including radiation and reliability effects in emerging semiconductor technologies
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 7 hours ago
focus of your research will be on mining publicly available data repositories and use machine learning to discover linkages between heterogeneous biological, social, and environmental data and human
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infrastructure, with the state-of-the-art reinforcement learning and generative AI, to detect, prevent, and preemptively mitigate intelligent attacker vectors. Supportive Mentoring: The postdoc will be guided by
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infrastructure, with the state-of-the-art reinforcement learning and generative AI, to detect, prevent, and preemptively mitigate intelligent attacker vectors. Supportive Mentoring: The postdoc will be guided by
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degree (M.Sc.-level) corresponding to a minimum of four years in the Norwegian educational system is required. The candidate must have interest and solid background in software systems, machine learning
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or Machine Learning). The Master’s thesis must be included in the application. Ideal Candidate: Demonstrates experience or strong interest in modelling, programming, systems thinking, and qualitative