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programme Reference Number AE2026-0269 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2026-0269
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Posting Details Student Title Classification Information Quick Link https://chapman.peopleadmin.com/postings/41080 Job Number SE237324 Position Information Department or Unit Name Fowler School
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Machine Learning e Computer Vision; Knowledge of Deep Learning (i.e., Pytorch, Tensorflow, JAX) and Computer Vision (e.g., OpenCV, MATLAB) frameworks/toolboxes; Basic knowledge to develop and deploy edge
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Vision (CV): Proven ability to apply object detection and style classification using libraries like OpenCV. â— Cloud & HPC Infrastructure: Experience configuring and managing environments in AWS/Azure
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-learning architectures for sequential data (e.g., Transformers, graph neural networks, state-space models). Experience with OpenCV, GPU-accelerated inference, Docker, and modern software engineering
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ultrasound sensing and hyperspectral imaging is necessary. Proficiency in Python programming, particularly with Python libraries such as Spectral Python (spectral), NumPy, SciPy, and OpenCV and familiarity
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their applications via the University of Alicante e-Services Portal (https://seuelectronica.ua.es/ )--Trámites [‘Procedures’]--Procesos selectivos y de provisión [‘Recruitment processes’]--Solicitud de plazas de
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Institute of Fundamental Technological Research Polish Academy of Sciences | Poland | about 1 month ago
or OpenCV Specific Requirements The successful candidate will be expected to: • Design and perform high-content and live-cell imaging experiments using macrophages infected with fluorescently labelled
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Learning Video Understanding Multimodal AI Excellent programming skills in Python. Hands-on experience with: PyTorch Hugging Face Transformers OpenCV Experience working with deep learning models for image
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). Experience with human-factors instrumentation and data streams: eye tracking, physiological sensors, and motion capture. Familiarity with data/video coding tools and computer vision (e.g., OpenCV, scikit-learn