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Field
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? No Offer Description Segmentation of scenes and shots for multimedia content monitoring and analysis using artificial intelligence and deep learning techniques, including transition detection, key
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básica en análisis de datos. Programación en Python. Conocimiento de modelos de machine y deep learning. Nivel medio de inglés. Secondary school diploma, vocational training (FP), or Bachelor’s degree
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microfluidics, nano-electronics, nano-biomaterials, big data, and deep learning. Applicants must hold an M.D., Ph.D., or equivalent degree and have extensive postdoctoral experience, along with a strong
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characterized as an inability to emulate basic human vision skills. Despite significant advances in deep learning-based computer vision systems, many limitations still exist. The main objective of this project is
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Skills/Qualifications Completion of a Master's degree in the field of Deep Learning applied to images and video. Scientific publications in the area of attribute recognition in images or medical imaging
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in developing bioinformatics pipelines (Python/R/Bash) for genomic (NGS) and medical imaging data analysis, implementing artificial intelligence and deep learning techniques. - Experience in developing
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UNIVERSIDAD CATÓLICA DE MURCIA - FUNDACIÓN UNIVERSITARIA SAN ANTONIO DE MURCIA | Spain | about 1 month ago
. Through advanced Machine Learning and Deep Learning technologies, it seeks to automate agronomic processes, optimize resource use, and maximize production in a sustainable way. Main duties Design
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: ED431F 2025/32 Álvaro Leitao Rodríguez Job title: ED431F 2025/32 Álvaro Leitao Rodríguez Research line / Scientific-technical services: Deep Learning for numerical solutions Grant/funding period: START: 18
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Experience in programming, expertise in software for handling big data, with a special emphasis on deep learning methods, and especially language models. 30% Complementary Training Having knowledge of software
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and paleosols 3) train and test deep learning algorithms. You will be required to take responsibility for all the steps involved in the “Phytolith analysis” work package of DEMODRIVERS. This will