40 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "Imperial College London" positions at Linköping University in Sweden
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application! We are looking for a research engineer within the Division of Statistics and Machine Learning (STIMA) at the Department of Computer and Information Science. In this position, you will have the
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application! Your work assignments We are looking for a PhD student to work on the development of novel spatio-temporal machine learning methods. Our world is inherently spatio-temporal, i.e. physical processes
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, both over the wireless interface and within the core network, will be driven by AI and machine-learning applications. This research will develop efficient communication strategies to support
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meritorious include: Knowledge of machine learning, reinforcement learning, and optimization, Experience with multi‑modal sensor data (vision, force/torque, proprioception), Experience with simulation
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materials and technologies. Using advanced computational modeling and machine learning, we seek to elucidate the mechanisms governing the self-assembly of lignin in different solvents and the formation
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of full-time. Your qualifications You have graduated at Master’s level in biomedical engineering, electrical engineering, machine learning, statistics, computer science, or a related area considered
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world. We look forward to receiving your application! Your work assignments We are looking for a PhD student to work on the development of novel spatio-temporal machine learning methods. Our world is
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different backgrounds. This position requires that you have graduated at Master’s level in in computer science, media technology, computer engineering, human-computer interaction, visual learning and
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(Sensor Informatics and Decision-Making for the Digital Transformation). Read more about the Competence Center here: https://liu.se/forskning/seddit . The focus of this specific PhD project is to explore
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ecosystem applications within AgTech (https://agtechsweden.com/ ), search-and-rescue operations in challenging terrain, and intelligent surveillance for societal security. By combining machine learning with