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, and interdisciplinary research team, RE will develop and implement deep learning algorithms to analyze trap camera footage for wildlife monitoring and conservation efforts. Job Responsibilities
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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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criteria Experience in writing documentation on the topic of Deep Learning Website for additional job details https://www.utcluj.ro/media/jobs/2025/DOC154_GAlboYR.pdf Work Location(s) Number of offers
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University of Oslo as a PhD Research Fellow in Deep Learning for geoscience imaging! PhD Research Fellow in Deep learning for subsurface imaging Apply for this job See advertisement About the position Position
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UNIVERSIDAD CATÓLICA DE MURCIA - FUNDACIÓN UNIVERSITARIA SAN ANTONIO DE MURCIA | Spain | 18 days 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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building a positive environment to grow and groom future business leaders. And we are looking to add to our BIZ family! To learn more about the NUS Business School, please visit https://bschool.nus.edu.sg
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learning systems, among others. Successful candidates will be responsible team players and passionate on cutting edge computer vision and machine learning technologies, as well as possess deep understanding
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control framework for microfluidic live-cell analytics in close collaboration with partners at HZI, Helmholtz Munich and HHU. Your tasks in detail: Establish deep-learning–based segmentation, species
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with an interest in the eukaryotic cytoskeleton. The candidate should be eager to learn new techniques and eventually be able to drive the project. We offer a friendly environment of a young group with a
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. Project background We are excited to announce an interdisciplinary PhD opportunity focused on mechanochemical processes driving radical formation and redox cycling in the deep subsurface, with implications