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Field
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design and implementation of visual cues detection on video datasets (face and gesture), context-aware multimodal analysis, machine learning/self-supervised learning for automatically detecting subtle
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learning* Technical qualifications: For bench scientist : expertise in mouse models of cancer, functional in vitro assays, experience with alveolar Type 2 organoid cell culture, experience with tissue
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mathematical modeling framework to find the optimal operation strategy for public transport services with autonomous vehicles Conduct computer programming to verify the efficiency of the designed solution
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, alignment, evaluation). Design multi-MLLM collaboration methods (knowledge transfer/distillation, federated learning). Build efficient training/benchmark pipelines and report results with clear metrics. Apply
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Is the Job related to staff position within a Research Infrastructure? No Offer Description We are seeking an ambitious candidate to develop Machine Learning models and frameworks for time series
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command of data wrangling, cleaning, and large-scale dataset management. Machine Learning/Deep Learning: Experience with PyTorch, TensorFlow, or Hugging Face; embedding models; and model validation
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estimation to begin in Spring/Summer 2026. The successful applicant will develop and implement data-driven tools, underpinned by scientific machine learning and reduced-order modeling, for ocean state
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Qualifications Experience with machine learning and AI models. Ability to communicate clearly with colleagues, Data presentations Scientific publication experience Special Instructions Priority Application Review
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analysis, PDE-constrained optimization and optimal control, numerical analysis and scientific computing risk-averse and fractional models, digital twins and data-assimilating models, machine learning and
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. Machine learning algorithms and physics of failure modelling LanguagesENGLISHLevelExcellent LanguagesFRENCHLevelBasic Additional Information Benefits MSCA Postdoctoral Fellowships enhance the creative and