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complex, high dimensional and high-volume datasets. Uses data preparation, modeling and predictive modeling, analysis, processing, algorithms, and systems. Applies knowledge of statistics, machine learning
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engineeringEducation LevelPhD or equivalent Skills/Qualifications We are seeking a scientist with: Expertise in image-based biological tissue modeling and simulation Good command of deep learning Expertise in coding and
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materials according to the Lambert–Beer law, thus enabling an accurate description of PEC device behavior. In parallel, the coupling between kMC and CFD simulations will be achieved through machine learning
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for vehicle applications; Abilities in using Finite Element modeling and analysis; Knowledge of injury biomechanics; Knowledge of Artificial Intelligent (AL) and Machine Learning (ML) techniques; and Abilities
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Institut Pierre Louis d'Epidémiologie et de Santé Publique (IPLESP) | Paris La Defense, le de France | France | about 2 months ago
a postdoctoral researcher to work full-time on the DiscoReel project. The postdoc will work on developing machine and deep learning methods for epidemic modeling, integrating them with mechanistic
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Remote Sensing; Machine Learning Models for Predicting Wildfire Spread; Wildfire Risk Assessment Through Multi-Modal Data Integration; Automated Vegetation and Fuel Load Mapping Using Computer Vision; AI
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Lab applies rigorous evaluation and modeling methods, including natural and field experiments, randomized controlled trials, behavioral economics, and machine learning, to help policymakers identify and
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- 4 Additional Information Eligibility criteria Required skills: strong experience in TVB modeling, experience in fitting models to human data, strong level of autonomy, solid knowledge of machine
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Description Completion of doctoral thesis related to: Process and analyze experimental data. Develop predictive models using deep learning. Train, validate, and optimize neural networks (CNNs, etc.) applied
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constraints such as electromagnetic interference (EMI), thermal stability, and mechanical durability. In parallel, the project will refine and optimize existing machine learning models for fault detection and