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unprecedented sensitivity for cavity optomechanical searches for new physics, including high-frequency gravitational waves and vector dark matter. About your role: FEM-based design and simulation
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application of dynamic mathematical modelling approaches to simulate the spread of infectious agents in human populations. The Unit coordinates the Interdisciplinary Center of Mathematical Modelling
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Postdoctoral Researcher in Natural Language Processing and Digital Humanities (18 months, full-time)
research task is to model semantic change and conceptual structure using Natural Language Processing. We will build customized NLP pipelines for premodern Greek and humanistic Latin, train and evaluate word
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School graduates over a thousand students who are ready to take on great ambitions and challenges. For more details, please view: https://www.ntu.edu.sg/eee We are seeking a Senior Research Fellow (SRF
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-informed models simulating system behaviour and providing decision-relevant insights Translating methods into decision-support prototypes and case studies in collaboration with academic and industrial
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theoretical and computational soft-matter physics and biophysics. The successful candidate will work primarily with Dr. Matej Kanduč on research topics related to molecular dynamics (MD) simulations
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systems in the research project, including testing and troubleshooting. Implement and test machine learning models, which may involve data preprocessing, model training, and evaluation. Create and maintain
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experiments Perform high-speed optical and thermal diagnostics Simulate electric fields and develop mechanistic models Publish high-impact research outcomes Job Requirements: PhD in a relevant engineering or
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engineering practices. Oversee and define complex computer models and simulations to evaluate engineering concepts, verify designs meet performance and interface requirements, and propose approaches and
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Sorbonne Université SIS (Sciences, Ingénierie, Santé) | Paris 15, le de France | France | 18 days ago
dynamics simulations of biomolecules in solution – using models of about 100 000 atoms – that provide a data set to train stochastic low-dimensional models (Langevin equations), based on diffusion on a