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Field
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technology be designed and evaluated so that it is usable, acceptable and aligned with users’ communication preferences and everyday lives? Your role Your PhD will primarily focus on computer vision and
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well as a wise use of machine learning methods. The candidate should hold an MSc degree in Applied Physics, Electrical Engineering, or the equivalent. The PhD position is firmly embedded in a physics
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) in computer science, artificial intelligence, data science, applied mathematics, physics, electrical engineering, or a related field. You have a solid background in machine learning; experience with
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, classics, gender studies, political science, and international studies—with cutting-edge data science techniques, including Earth Observation (EO) data analysis, machine learning, large-scale collation and
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discipline. Desirable Experience in machine learning, deep learning, data analysis, numerical modelling, or scientific programming (such as Python, MATLAB, or R) is desirable. Knowledge of hydrodynamic
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University of Science and Technology (NTNU) has a vacant position as PhD candidate in the field of machine learning for materials science. Your immediate leader will be the Head of Department. About the
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discipline. Essential Good programming skills, preferably in Python/C#. Experience with machine learning, deep learning, or experimental AI evaluation. Interest in secure distributed AI, federated learning
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improved using machine learning techniques. The developed techniques will be applied to metrology of semiconductor samples. Job requirements You are an enthusiastic candidates with a ‘drive’ for applied
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Engineering at the University of Sheffield. A leading centre for machine learning, robotics, and autonomous systems. The student will join a research group working at the interface of machine learning, control
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Knowledge of machine learning, Large Language Models (LLMs), Vision Language Models (VLMs), or generative AI Experience with Retrieval-Augmented Generation (RAG), AI agents, model-driven engineering, DevOps