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, process simulation, etc.) Data-driven modelling and/or artificial intelligence modelling ability (e.g. statistical machine learning, deep learning, generative AI, large language models, etc.) Familiarity
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is decentralized or only partially observable? Depending on the research direction, you may employ techniques from mathematical modelling, machine learning, uncertainty quantification, distributed
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emerged as a new learning paradigm in AI. These models learn from large datasets through self-supervision and have proved to generalize across many applications. Successful examples of foundation models
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6G and beyond. The project combines analytical modelling, system simulation, photonic integrated circuit design, machine learning, and experimental validation using state-of-the-art communication
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15 Aug 2026 Job Information Organisation/Company Eindhoven University of Technology (TU/e) Research Field Computer science » Programming Engineering » Computer engineering Engineering » Electrical
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interactions between individual cells. Where to apply Website https://www.academictransfer.com/en/jobs/362788/post-doc-learning-interactions-… Requirements Specific Requirements PhD Degree in Physics Preferably
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PhD candidate you will develop new ways to extract cosmic-ray physics from KM3NeT data. You will design and characterise reconstruction methods—both machine-learning-based and traditional
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statistical, machine learning, probabilistic modelling and signal processing techniques to longitudinal wearable sensor datasets. • Collaborating with clinicians, data scientists, engineers, researchers
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Health Data Sciences and Informatics (OHDSI, https://ohdsi-europe.org ) initiative, dedicated to bring out the full value of observational health data through the OMOP Common Data Model and large-scale
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generation of experts skilled in the combination of Operation Research and trustworthy Machine Learning. CoRDS goes beyond the state-of-the-art DDO methods by proposing decision support frameworks that combine