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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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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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multilingual or speech impairment contexts. Programming Skills Strong proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow. Experience with web development (e.g., FastAPI, Flask
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Experienced in A.I., Deep Learning, and Simulations. Physical Requirements & Working Conditions Degree Requirement Listed degree qualification is required at time of application Posting Information FLSA Status
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programmes. We are especially keen to hear from applicants with expertise in areas such as Machine Learning and Deep Learning, Generative AI, Data-Centric and Responsible AI, or AI for real-world applications
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Scientist / Scientific assistant – Tree species detection using deep-learning Are you an ambitious data scientist with strong analytical and numerical skills, and expertise in geomatics, remote sensing, and
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been established. This position will focus on the further development of various, machine learning and deep learning models to study molecular mechanisms and cellular phenotypes caused by the etiology
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technologies-including gradients, RF coils, field cameras, image reconstruction strategies, and AI/Deep Learning approaches-and to integrate these advancements into the Center's research infrastructure. Key
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, seeks to recruit a research assistant to work on the intersection of compilers and deep learning. Many companies, such as Google, Facebook, and Amazon are building new specialized programming frameworks
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or equivalent) Strong programming proficiency in Python Experience with deep learning frameworks such as PyTorch and/or TensorFlow Experience using data science libraries (e.g. NumPy, Pandas, SciPy, scikit-learn