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of the Quantum & Computer Engineering (QCE) department is looking for a highly motivated PhD candidate who is eager to work on AI based solutions for predictive inteligence for MRI scanning. The candidate will
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-scale compound drivers. We will leverage machine learning methods to bridge the gap between drivers at coarse model resolutions and impacts captured by high-resolution observations. Job description Arctic
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applicants should have a strong academic record with a solid background in Machine Learning. Knowledge of Vision-Language-Action models and Novel View Synthesis techniques is a strong plus. Good programming
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to state-of-the art AI/machine-learning, from modelling to measuring emissions and climate effects, noise and noise propagation. Job requirements The PhD position is funded by the Horizon-Europe TUNED
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, silicon-proven AI/ML accelerator for transmitter error correction (digital predistortion/calibration). Your work will sit at the intersection of machine learning, DSP, and digital IC design, and you will
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. Methodological Approach Candidates will develop and apply state-of-the-art machine learning techniques, including deep learning, representation learning, variational autoencoders, and graph-based models. A strong
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physical). Solid background in programming and experience with machine learning. Knowledge of participatory design and co-creation methodologies. Ability to learn independently and passion for research