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Field
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-models, thereby avoiding double counting of effects, • developing and evaluating temporal machine-learning models for sequence-to-sequence prediction of fuel behaviour, • extending surrogate models
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industry. Our group combines precision experiments, advanced imaging, and modeling to uncover the physics of tin droplets under extreme conditions of laser irradiation. We have established a strong track
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‑on experience in AI / machine learning development (excluding PhD); proven expertise in machine learning and generative AI methodologies (in the range of: LLMs, RAG systems, agentic AI, feature engineering, model
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Engineers usually want predictability. This project embraces chaos! – Excited about control theory? Then join us to build the math of chaotic sampling for greener and more secure control systems
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: PhD in Chemical Engineering or related field Required Education: 1 year of prior research experience on multiscale modeling, hybrid modeling, and model-based control or related fields Desired Experience
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prediction, physics-compliant motion generation, whole-body control, safe robot learning, hierarchical planning for healthcare environments, and the translation of generative models into reliable physical
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Centar izvrsnosti MARBLE drustvo s ogranicenom odgovornoscu za istrazivanje i razvoj | Croatia | 24 days ago
Cooperative trajectory planning and coordination of UAVs, USVs, and AUVs/ROVs Optimal control and Model Predictive Control (MPC) for autonomous and multi-robot systems Convex and non-convex optimisation methods
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, and control (such as CNNs, RNNs/LSTMs, autoencoders, physics-informed neural networks, anomaly/outlier detection, uncertainty quantification, model predictive control). Documented knowledge and
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, and traceability in accordance with the GDPR and the EU AI Act. Integrate predictive virtual biopsy models in distributed environments. Lead pilot experiments and monitor the convergence of federated
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the following work packages: WP2: Urban Digital Twin, Data Services and Security and, more specifically, in the following task: Task 2.1: Common Information Models and Urban Data Spaces The task focuses