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eine Verlängerung auf insgesamt maximal 4 Jahre möglich. Über das Team Werden Sie Teil der Forschungsgruppe „Responsible Machine Learning (ML)“ an der Fakultät für Informatik. Unter der Leitung von
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Fellow to develop and evaluate artificial intelligence methods for physical medical procedures. The fellow will design and implement machine learning models to analyze procedural data, support clinical
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publishing in peer-reviewed scientific journals Your Profile Master’s degree in electrical engineering, physics, computer science, or a related field Strong academic background in embedded AI and in the
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systems. Your Profile Bachelor’s degree and currently enrolled in a Master’s program in electrical engineering, physics, or a closely related field Basic understanding of device physics, analog/mixed
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website: https://www.irc.ugent.be/groups/maelfait-lab Research Project Nucleic acids are potent triggers of immune responses. The presence of virus-derived RNA or DNA molecules activates nucleic acid
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laboratory environment and following specific clean room protocols Master`s degree in physics or electrical engineering or a related field Willingness to work in laboratory and cleanroom environments
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Human-Centered Artificial Intelligence and the SLAC Machine Learning Program. KIPAC also has strong ties and active collaborations with theorists at LITP @ Stanford and SLAC. The positions offer a
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AI-enabled digital technologies for the resilient operation of power systems School of Electrical and Electronic Engineering PhD Research Project Self Funded Prof Xin Zhang Application Deadline
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Autonomous Scalable Knowledge Extraction and Decision Making for Complex Systems and Dynamic Environments School of Electrical and Electronic Engineering PhD Research Project Self Funded Prof
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, Biomedical Engineering, Electrical Engineering, Bioinformatics, Statistics, Applied Mathematics, Physics, or a closely related STEM field. Demonstrated experience developing AI and machine learning