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programming skills (primarily in Matlab, Fortran, or others) and experience in numerical modelling and time series analysis, Fluent command of English, both spoken and written (sufficient for independent work
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efficiency and reliability. Strong background in data analytics, leveraging insights to drive operational improvements and predictive maintenance. Experience in control strategies and automation, ensuring
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Sorbonne Université SIS (Sciences, Ingénierie, Santé) | Palaiseau, le de France | France | 2 months ago
appelé Cloud-Resolving Model (CRM). Il s'agit d'un modèle atmosphérique non hydrostatique simulant un domaine local relativement petit (quelques centaines de kilomètres, comparé au rayon de Jupiter de 70
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-driven and machine-learning approaches for the analysis and integration of complex neural and movement data, supporting new insights into the mechanisms underlying human motor control and rehabilitation
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Sharing – Building a federated data space to enable responsible data integration and cross-project learning. AI & Modelling – Using shared data to power advanced models that help describe and predict
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-temporal machine learning method development, including: generative models for grid-based and particle-based spatio-temporal data; controlled generation methods for data assimilation; and graph-based multi
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to identify trends, variances, and opportunities for improvement. Support the development of long-term financial strategies and risk assessments. Builds predictive models and forward-looking analyses
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, based on detailed studies of Earth and the solar system, is developing predictive models to identify habitable planets around other stars. Within three different research themes: (1) Planets and Early
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contexts. This work will directly support the development of AI models to predict off-target effects across clinically relevant cell types, including primary cells and 3D organoid systems. Responsibilities
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interest in social science applications, and with strong competence in statistics and machine learning. The successful candidate will develop predictive models using machine learning and work alongside other