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Field
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regression to represent unknown dynamics for model predictive control. Despite the practical success, there are still many theoretical open questions regarding scalability, uncertainty bounds and deriving
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Gaussian process regression to represent unknown dynamics for model predictive control. Despite the practical success, there are still many theoretical open questions regarding scalability, uncertainty
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real-time, predictive control frameworks for ankle exoskeletons that regulate calf muscle-tendon forces during human locomotion. A central goal is the short-term (millisecond-scale) estimation and
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at Tilburg University, in collaboration with the Faculty of Military Sciences and the Joint Sigint Cyber Unit, invites applications for a fully funded postdoctoral position focusing on predictive modelling
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Max Planck Institute for Solar System Research, Göttingen | Gottingen, Niedersachsen | Germany | 8 days ago
techniques have enormous potential for the modeling, prediction, and control of nonlinear systems governed by partial differential equations. This project will focus on developing machine learning methods
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-control vs cohort, etc.). Strong grasp of statistical/ epidemiological principles e.g. risk prediction and survival/time-to-event modelling. Experience with uncertainty aware evaluation: confidence
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-driven frameworks for multi-scale modeling, multi-objective optimization, and predictive control of complex chemical and biochemical processes. The research will contribute to next-generation smart
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, predictive models), AI‑driven network functions (closed-loop control, optimization, anomaly detection, intent resolution). You are familiar with cloud-native development (Docker, Kubernetes), CI/CD pipelines
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applications in chemical and pharmaceutical manufacturing; data-driven modelling and machine learning applications in process industries; advanced process control (APC); model predictive control (MPC); digital
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of artificial intelligence, multi-omics data integration, and functional genomics, aimed at predicting synthetic lethality in cancer - including representation learning, nonlinear embeddings, and predictive