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or experience in digital image processing, computer vision, machine learning, data science, or a related field. Familiarity with Python libraries such as NumPy, OpenCV, Matplotlib, or similar scientific computing
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. — Excellent communication skills and a user-centred approach. The following will be particularly valued — Experience in analysis using machine learning or artificial intelligence applied to biomedical images
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-VIS-NIR). Experience in hyperspectral data processing (HMSPL, μXRF, μXAS) and statistical analysis (clustering, machine learning) is preferred. Familiarity with fossilization processes and taphonomic
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multiple modalities of medical imaging (e.g. fundoscopy images, OCT scans, MRI, CT, X-ray and digital pathology). We bridge the gap between machine learning research and clinical practice through fruitful
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Graph Deployment & Validation Report (Prototype) Where to apply E-mail [email protected] Requirements Research FieldEngineering » Computer engineeringEducation LevelMaster Degree or equivalent Skills
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publications and presentations · Ensures the accuracy and reliability of image data and analysis methods, implementing validation processes when necessary · Will work as a team to optimize machine learning
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» Computer engineering Researcher Profile First Stage Researcher (R1) Positions Other Positions Application Deadline 20 Oct 2026 - 17:00 (Europe/Paris) Country France Type of Contract Temporary Job Status Full
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, preferably in Python, and experience with machine learning or deep learning. Experience in computer vision, digital pathology, whole-slide image analysis, self-supervised learning, foundation models, multiple
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data acquired by mobile road monitoring systems using heterogeneous sensors, such as images, laser profilometers, GPS, and audio data, will integrate machine learning, computer vision, and image analysis
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experiments. Conduct experiments related to deepfake detection and computer vision. Prepare, preprocess, and analyze image and video datasets. Train and evaluate deep learning models using performance metrics