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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 6 days ago
]. This requires interactively defining a template per flower, and is not suited to multi-layered petals, as in case of a rose. This postdoc position is concerned with a data-driven approach that learns
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: Applied mathematics; Machine Learning; Mathematical Modelling Appl Deadline: 2026/03/24 10:59 PM UnitedKingdomTime (posted 2026/03/18 04:00 AM UnitedKingdomTime, listed until 2026/04/01 04:59 AM
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generation, media forensics, anomaly detection, multimodal learning with an emphasis on vision-language models, computer vision applications for space. Key responsabilities: Shape research directions and
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demonstrated experience in computer vision or analysis of pathology images. The appointees will participate in a multidisciplinary collaborative research project related to development of deep learning model
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://www.maynoothuniversity.ie/physics/our-research . This position is part of the CARINA project which is funded through a Research Ireland Frontiers of the Future grant. CARINA stands for Combining Machine Learning with
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. The successful candidate will be employed at the Department of Computer Science of the University of Luxembourg and have access to high-performance computing resources suitable for large-scale machine-learning and
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, Environmental Science, Remote Sensing, or related field Experience in atmospheric modeling, satellite remote sensing, or machine learning Programming skills (Python or R) Strong publication record Where to apply
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the knowledge acquired during the PhD with team members and acquire new knowledge. - Engage with the Local team at LIPN and the wider national community working on proof theory, programming languages and
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Description Our Commitment Texas A&M University is committed to enriching the learning and working environment by promoting a culture that respects all perspectives, talents & lived experiences. Embracing
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for the analysis of hyperspectral imaging data applied to pictorial layers, based on coupling physical radiative transfer models (two-flux and four-flux approaches) with machine learning methods. The researcher will