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-driven 3D motion understanding and generation in the following ways: Developing machine learning methods to decode EEG-based motor imagery for 3D human motion reconstruction, focusing on latent diffusion
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electrical engineering, control engineering, computer science, applied mathematics or a related field. The successful candidate will have expertise in at least in one of: Machine learning in the context
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to migration-related diversity. The position contributes to advancing methodological innovation through the creative and reliable use of machine learning, AI, and other algorithmic techniques in qualitative
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more than five years ago at the time of accepting the position (a net period of time, which does not include parental leave, military service etc.) good skills in spoken and written English prior experience
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efficiency and the safety of operators and equipment. Science objectives: 1) Development of innovative machine learning models that require minimal data by leveraging simulations and domain knowledge, and
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Project tasks and objectives: Industry objectives: To investigate sensor configurations and machine learning methods for sensor fusion-based machine perception for real-time operation, including
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(PyTorch, Tensorflow etc.) Knowledge of multi-agent systems and autonomous agent modelling Expertise in Machine Learning and Artificial Intelligence We consider the following as an advantage: Willingness
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will design and implement novel computer vision and machine learning methods for “sensorized” cameras that extract medically relevant features without transmitting raw video. You will evaluate algorithms
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, molecular and mesoscale level particle-based techniques, continuum modeling, statistical approaches and machine learning. The successful candidates are expected to lead an outstanding independent research
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with a background in Language Technology, Machine Learning, or Language Typology who are interested in automatic classification and analysis of hundreds of languages to undertake a PhD project exploring