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Field
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functionalities that can further improve operational performance, such as the integration of predictive models, orbital dynamics knowledge, or drag-aware optimisation strategies to enhance manoeuvre timing and
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The main objective of the project is to develop novel, interpretable predictive models for response to immunotherapy in patients with advanced melanoma, based on the functional activity of gut fungi
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or robotic systems Knowledge of system integration, instrument control, workflow automation, and data acquisition Experience developing and applying AI/ML methods, including predictive modeling, active
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Post Doctoral Researcher Rinn Artificial Intelligence – Research & Innovation in Data Science and AI
patient risk prediction using machine learning (with experience in particular in radiomics and transcriptomics) • Multi-omics for non-cancer health screening applications, • Machine learning modelling
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learning, understand their mathematical foundations, and connect them to space-related technologies and missions. The focus is on building rigorous models that explain and predict the behaviour of modern
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modeling, or real-time data analysis. Familiarity with data visualization, reproducible research workflows, version control, and collaborative coding practices. Interest in translating computational methods
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Bring physics into world models — and make embodied agents fast, reliable and ready for the real world! Join us! World models are controllable, physics- and mechanism-grounded simulators of reality
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to post-process characterization. This environment enables the creation of high-fidelity digital twins and AI-ready datasets that support real-time monitoring, predictive modeling, and process optimization
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National Energy Technology Laboratory (NETL) | Morgantown, West Virginia | United States | about 1 month ago
modeling (ROM) Some experience with various programming tools (Python, MATLAB, C++, C) Some familiarity with machine learning: predictive modeling, anomaly detection, supervised learning, deep learning
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robotics – reinforcement learning, whole-body model predictive control (MPC), and differentiable optimal control – to simulate human balance and step recovery in urban transport scenarios. The goal is a