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experts in the field of protein engineering, protein production, affinity ligand design and characterization, and machine learning for protein design. This unique PhD position is a 4-year collaborative
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, semiconductor technology and metrology that are part of the SWEET project. About us The position is hosted by the Microwave Electronics Laboratory at MC2 where the PhD student will have access to several
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that enhance the quality and efficiency of forest management planning. The PhD student will combine remote sensing with machine learning to detect cultural remains, predict terrain accessibility, identify
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cybersecurity team at Luleå University of Technology and also our partner within Cybercampus Sweden, RISE. We will use methods and technologies including expert systems, evolutionary algorithms, machine learning
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Merits: Experience with Matlab Prior coursework or project experience in railway mechanics Background in signal processing Knowledge of machine learning techniques Main responsibilities Your primary
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, which is crucial for rutting, using machine learning. Second, we will develop new systems to integrate data from radar and lidar sensors mounted on drones and forestry machines to improve future real-time
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machine learning techniques into a modern AI planning system. The project will involve both theoretical and experimental work As a PhD student, you devote most of your time to doctoral studies and the
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of quantum chemical calculations (DFT) is advantageous. An interest in machine learning and AI-based methods, as well as programming skills in languages such as Python or MATLAB/Simulink, is beneficial
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Sciences division. This multidisciplinary team utilises a combination of machine learning and mechanistic modelling to derive models and scientific insights from data, which both support and enhance drug
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for Computer Vision conducts research and education in machine learning for computer vision at the undergraduate, advanced, and PhD levels. CVL has been identified as an outstanding Swedish research environment