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French National Institute for Health Research (INSERM) | Lille, Nord Pas de Calais | France | 3 months ago
bioinformatics workflows in Python for the analysis of transcriptomic, proteomic, single-cell transcriptomic, and interactome datasets. Design and implement Big Data and machine learning approaches using Python, R
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Cardioembolic Stroke Risk Stratification using AI Accelerated Patient-Specific Blood Flow Simulation
wall motion will be extracted from dynamic 4D flow MRI (20 phases per cycle) via an in-house deep learning-based segmentation tool. Mean flow velocities in the pulmonary veins have also been measured by
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in the field of operational research and/or machine learning algorithms would be a plus. In accordance with the commitments made by the CEA to promote the integration of disabled people, this job is
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possess expertise in a broad range of topics in condensed matter, including magnetism, superconductivity, topological matter, and low-dimensional quantum matter. The candidate will learn and master a
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) to join our team and contribute to ongoing research projects. Key Accountabilities Acquire technical and theoretical knowledge through close supervision and training; Perform cell culture and image-based
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of language learning and experience of doing qualitative research Ability to work in a multidisciplinary research environment Good analytical and problem-solving skills Experience of and interest in
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their dynamics to be formulated as systems of linear ordinary differential equations. Bayesian Optimization and Reinforcement Learning methods will be employed to solve the inverse problem of shape and flexibility
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(NIMS, Seagate). The student will be trained on a femtosecond laser bench, and learn extensively about aspects such as spintronics, ultrafast optics, near field microscopy, material growth and clean room
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The detection of out-of-distribution (OoD) samples is crucial for deploying deep learning (DL) models in real-world scenarios. OoD samples pose a challenge to DL models as they are not represented