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LevelMaster Degree or equivalent Skills/Qualifications Solid background in Machine Learning and Deep Learning. Experience or interest in agentic AI frameworks (e.g., LangChain, LangGraph, AutoGen, or similar
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data and deep learning methods to assess canopy cover, quality, carbon stocks, and ecosystem services. Mandatory requirements: PhD in areas related to forest resources, remote sensing, data science, or
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missions operated by LATMOS. The postdoc will employ deep learning approaches using satellite data and ground stations. -Understanding the infrared data from the IASI mission and identifying the channels
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on AI-assisted reverse engineering of integrated circuits for hardware assurance and intelligence analysis. The project is conducted within the Deep Learning for Perception and Data Science, Safety and
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processes, the foundations of deep learning. Experience coding with deep learning libraries such as Pytorch/JAX is essential. Fluent written and spoken English skills as well as contributions to the group
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Are you passionate about combining the directed evolution of diverse biomolecules with deep learning approaches and contributing to the development of better (bio)catalysts and drugs? We
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knowledge for a better world. You will find more information about working at NTNU and the application process here. About the position We have a vacancy for a PhD candidate in machine learning
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(payable 14 times per year) Responsibilities The applicant is expected to establish an own research group with focus on advanced machine learning and deep learning techniques for remote sensing applications
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to stay at the forefront of medical science, and educators to advance learning. We are proud to be part of progress, working together with the communities we serve to share knowledge and bring greater
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school, and taking part in the supervision of students. A limited amount of teaching may be included (max 20%). Requirements PhD degree in machine learning, scientific computing, statistics, physics or a