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Préhistoriques (HNHP, UMR 7194) laboratory is a joint research unit under the supervision of the CNRS, the MNHN, and the UPVD. Its mission is to study the biological and behavioral evolution of hominins over
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. Guidance on writing, presentation, and career development. Flexible working hours. A shared interest in producing high-quality research results. Where to apply Website https://www.academictransfer.com/en
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to develop an AI-enhanced Digital Twin framework for predictive maintenance and energy optimization in industrial environments. The research will investigate the integration of Industrial Internet of Things
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solution due to its high positioning accuracy, low latency, and robustness in complex environments. This PhD project aims to develop intelligent UWB-based positioning and navigation systems for industrial
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user studies, develop novel algorithms, build immersive/augmented realities, and validate your solutions in real-world settings. This PhD is ideal for candidates interested in one or more of the
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different incentives, mechanisms and regulatory scenarios, evaluating their performance with respect to different objectives and their trade-offs. Developing decentralized and bi-level algorithms to help
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record. Mathematical skills in linear algebra, calculus, and statistics for algorithm development and data analysis Evidence of research output including high quality publications, conference contributions
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by recent deepfake misuse and strict regulations such as GDPR. We aim to develop a real‑time, privacy‑preserving camera system that anonymizes individuals directly on the device. Instead of blurring
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Systems Engineering (ICE-1), our focus is on developing models and algorithms for simulating and optimizing decentralized, integrated energy systems. These systems are characterized by the high spatial and
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-rich aerial manipulation in unstructured and dynamic environments, particularly in close proximity to objects. The developed algorithms will be validated through real-world experiments that enable