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Field
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: Statistical model development: Led the development of advanced statistical models and machine learning algorithms for forecasting precipitation and temperature in Morocco. This will involve data analysis, model
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recommendation mechanisms based on semantic analysis and natural language processing, with the aim of facilitating collaboration and convergence of proposals. Developing and training NLP algorithms in multiple
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, to enable scalable quantum algorithm development and quantum-HPC codesign. What is Required: PhD in Computer Science, Computational Science, Applied Mathematics, or a related field awarded within the last
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person will focus on either using and/or developing Vlasiator. Prior knowledge in at least one of the following areas is required: GPU technologies, high-performance computing, parallelisation algorithms
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algorithms and techniques and design, implement, test, and maintain software/tools embodying those methods. You will prepare and submit grant proposals to external funding bodies. This position will also
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” wherein messages including emotions are incorporated into the movements of collaborative robots. Key Responsibilities: Design, implement, and test real-time multi-objective motion planning algorithms
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Laboratoire de Physique des Interfaces et des Couches Minces (LPICM), UMR CNRS/École Polytechnique, | Palaiseau, le de France | France | 2 months ago
(denoising, Mueller matrix calculation/decomposition) and AI-based diagnostic algorithms using machine/deep learning. The primary challenge will be to deliver practitioner-relevant cervical images in under 0.5
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Fluid-Structure Interaction to focus on developing computational algorithms for fluid-structure interaction problems including the multiphysics effect of electromagnetism. The Role: As a Research Fellow
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biomarkers, designing algorithms that capture temporal change, and incorporating clinician-informed explanations to build trust and transparency into predictions. Working closely with experts in ophthalmology
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benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: Research and develop novel reliable deep learning computer vision algorithms for the detection and quantification of GIM lesions