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) for engineering systems and structures, as well as expertise in machine learning, stochastic modeling, and Bayesian statistics. Programming Skills: Proficiency in programming languages such as Python, C, or R
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degree in engineering, mathematics, or a related field, with a strong background in prognostics and health management (PHM) for engineering systems and structures, as well as expertise in machine learning
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analytics (statistical models, machine learning, uncertainty quantification) to monitor and predict cycling travel conditions from various perspectives (safety, crowding, travel time, comfort, etc
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comprehensive and trustworthy AI models for subtype prediction, significantly influencing clinical decisions and personalized treatment strategies. The current project funded by NWO is a continuation of the
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, Interns and Visiting Researchers, as applicable; develop and evaluate AI/ML models to identify, quantify and predict climate change impacts relevant to adaptation, resilience and mitigation on the topics
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Professor who dares to push boundaries—an ambitious leader with expertise in applying machine learning and artificial intelligence to unlock the complexity of biological systems. Your colleagues: At MaCSBio
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can focus on learning for planning, risk-aware motion planning under uncertainty, learning of interaction models, multi-robot learning, multi-modal prediction models, or other related topics
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strategies (e.g. predictive or machine learning approaches) to improve performance and reduce costs. Collaborating with industrial partners on design optimization, life-cycle analysis, and business case
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of the model predictions. Validation and evaluation of the RFBs with optimized hierarchical electrodes. Job Description The advertised subproject is fully funded by the Marie Skłodowska-Curie European Training
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Village to calibrate and validate models. Investigating control strategies (e.g. predictive or machine learning approaches) to improve performance and reduce costs. Collaborating with industrial partners