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and apply AI and machine-learning methods to infer interaction networks from acoustic co-occurrence and activity patterns, and analyse their structural properties to link topology to response diversity
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demonstrated its potential to support people with limited arm and shoulder function. Your task will be to explore and develop an AI-enhanced Human-Machine Interface (HMI) that enables a more intuitive and
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, electrical engineering, mechanical engineering, chemical engineering, control engineering, or a related discipline. A strong foundation in at least one of: electrochemical or energy-system modelling
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Responsible Machine Learning (ML) Group at the Faculty of Computer Science. Led by Prof. Dr. Martin Pawelczyk, who recently joined the University of Vienna from Harvard University, our research sits at the
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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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(MSc., M.Eng. or equivalent) in Computer Science, Electrical Engineering, Robotics, or related field You bring: A strong foundation in machine learning , including classification and regression, model
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is focused on using spatial profiling and machine learning of human specimens in combination with functional experiments in animal models to understand cancer initiation, progression, and metastasis
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data-quality agents, predictive models that can transfer across machine families, prescriptive decision support, operational dashboards, and ensuring the delivery of methodologies, documentation
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Digitally enabled development of sustainable metamaterials to create circular alternatives to current unsustainable parts widely used in industry School of Electrical and Electronic Engineering PhD
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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