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theory, modeling, and AI-assisted optimization activities within the consortium. Reporting and dissemination of the results. Share this opening! Use the following URL: https://jobs.icfo.eu/?detail=1074
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Engineering. Experience with MLflow, Feature Store, Model Serving, or AI workflow orchestration. Experience with vector search, embeddings, or LLM-based application components. Familiarity with machine learning
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Postdoctoral Researcher in ML for Dynamical Systems Representation, Prediction, and State-estimation
cutting edge machine learning techniques for sequential data modelling, including Physics-informed Machine Learning and Koopman Operator-based representation framework, towards building interpretable
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combine density functional theory (DFT), molecular simulations, and machine-learning force field (ML-FF) development to uncover the factors controlling NHC–surface interactions and to model realistic
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this project, the candidate will be expected to explore a range of fundamental and applied problems in mathematical modelling of plant morphogenesis based on these approaches. Depending on their preferences and
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. The PhD candidate will combine materials science, computational modelling to design a novel framework that identifies optimal materials and AM processes based on performance, sustainability, and reusability
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://blog.nus.edu.sg/geospatialx/ ), based in the Geography Department at National University of Singapore, has conducted a series of infectious disease transmission and control studies. We are seeking to recruit
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Postdoctoral Researcher in ML for Dynamical Systems Representation, Prediction, and State-estimation
for sequential data modelling, including Physics-informed Machine Learning and Koopman Operator-based representation framework, towards building interpretable predictive models for complex multi-physics dynamical
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of development stochastic models that explain the population behaviour of immune cells subject to controlled stimulation, you will collaborate in research that seeks to explain the weak inheritance features