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of estimators, test statistics, and predictions modelling dynamic relationships between brain activity and subjectively experienced pain at the individual level Research context The PhD is closely linked
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systems capable of selecting and combining models of different complexity, in order to better represent groundwater dynamics and improve large-scale predictions under climate change. Objective — The PhD
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 12 days ago
the prediction of vehicle flows, energy demand, and flexibility of electric vehicle fleets, with applications to energy and transportation systems. The work lies at the intersection of systems and control, data
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to crack initiation and assess the influence of the microstructure of Almelec alloys. The results will also be used to improve a predictive FEM model (Abaqus/Python) simulating crack initiation and
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sensitivity (by controlling field amplitude, frequency, and penetration depth). _ Implement MRP measurements under controlled stress (uniaxial and residual). _ Validate the model with experimental MRP data
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at Tilburg University, in collaboration with the Faculty of Military Sciences and the Joint Sigint Cyber Unit, invites applications for a fully funded postdoctoral position focusing on predictive modelling
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Scientific Software Developer to lead the development and public release of software for predicting excited-state X-ray and electron energy-loss (EEL) spectra using Bethe–Salpeter Equation (BSE) and Time
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inefficiencies and fragmentation across teams Enable more predictable and scalable support to research activity To support the implementation and consolidation of this model, ICFO is seeking a Coordinator of
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unit dedicated to advancing the understanding, monitoring, and predictive modelling of modern engineering structures. Research within the department on Structural Health Monitoring (SHM), non-destructive
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Max Planck Institute for Solar System Research, Göttingen | Gottingen, Niedersachsen | Germany | 23 days ago
techniques have enormous potential for the modeling, prediction, and control of nonlinear systems governed by partial differential equations. This project will focus on developing machine learning methods