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to make a direct impact on patient care. About your role During machine perfusion, donor livers can be maintained outside the body, creating a unique opportunity to assess organ quality and deliver targeted
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that truly understands its environment. You have a master's degree in Computer Science, Artificial Intelligence or similar. You are interested in Logic, Machine Learning, Knowledge Graphs, Stream
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quantitative field. Good scientific programming skills, particularly in Python, are required. Experience with atmospheric dynamics, numerical modelling, machine learning, or large meteorological datasets would
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perform both empirical and theoretical work. You will learn how to collect and analyse data within your research area as well as communicate your results at national and international conferences and in
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of dynamic radar scenes. The project combines methodological machine learning research with experiments on real automotive sensor data. You will have access to research vehicles and advanced radar prototypes
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) Item 03: Proven experience in both programming (Python, R, etc.) and the use of data analysis tools, as well as artificial intelligence / machine learning techniques (punctuation: 22.5) Item 04
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, vegetation occlusion, and low illumination conditions; - Contribute to the definition of resilient perception architectures for outdoor robotic operation. 2. Machine learning-based resilient perception
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and memory systems. This effort is truly trans-disciplinary, drawing on biodesign/biotechnology, machine learning, and interaction design. This project builds on groundwork already underway in our group
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the ERC CoG PANDORA (Deep Multimodal Learning for Mining and Generation of Arguments). Where to apply Website https://emploi.cnrs.fr/Offres/Doctorant/UMR7271-SERVIL-002/Default.aspx Requirements Research
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different dyadic motor coordination tasks. A range of neurophysiological measures (EEG, ECG and fNIRS) as well as behavioural measures will be recorded simultaneously from both partners. Machine-learning