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Epidemiology of Malaria), led by Aimee Taylor. Using simulation-based inference (SBI) with deep learning, UniGEM aims to build a neural network to estimate epidemiological parameters of P. falciparum
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learning and physics, addressing key challenges in modern quantitative biology. The successful candidate will be responsible for: • Develop and train deep learning models (CNNs, ...) data to predict IPLSs
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missions operated by LATMOS. The postdoc will employ deep learning approaches using satellite data and ground stations. -Understanding the infrared data from the IASI mission and identifying the channels
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IRCM - Cancer Research Institute of Montpellier | Montpellier, Languedoc Roussillon | France | 3 months ago
Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description 🔬 Project Overview The PINKCC Lab develops deep learning, data
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have skills in eukaryotic cell biology, electron microscopy, and bioimage analysis. You have a basic knowledge in integrative structural biology, and in AI / deep learning approaches and/or sub-tomogram
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on developing deep learning methods for the reconstruction and physical analysis of ATLAS experiment data. The selected candidate will develop innovative analysis methods for the reconstruction and physical
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deep learning approaches, with a particular interest in developing methods capable of handling scarce or corrupted data, designing methods for specific imaging modalities, or understanding and
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subject The DEEPICE project aims to develop an automated workflow combining glacial geomorphology, remote sensing, DEM analysis and deep learning to detect and analyse subglacial bedforms at large scale
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on deep learning coupled with molecular simulations for the investigation of slow variables and transition pathways describing large conformational changes and reactive processes in complex biological
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 2 months ago
computer vision and/or audio(-visual) machine learning (e.g., multi-object tracking, speaker/source localisation, multimodal fusion). Experience with deep learning frameworks (PyTorch or equivalent) and