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PhD Neural Control of Vocal Pitch: Exploring the Intersection between Speech and Language Processing
expertise in speech motor control and vocal pitch processing, and Dr. Frank Tsiwah, who brings expertise in neural processing of language and machine learning techniques for linguistics research. Since its
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PhD Neural Control of Vocal Pitch: Exploring the Intersection between Speech and Language Processing
Dr. Frank Tsiwah, who brings expertise in neural processing of language and machine learning techniques for linguistics research. Since its foundation in 1614, the University of Groningen has
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Post-doc Machine Learning and Modelling of Perovskite Solar Cells (V24.0287) « Back to the overview Job description The University of Groningen is a research university with a global outlook, deeply
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for a highly motivated and qualified PhD student/researcher who will work towards developing new (machine learning and deep learning-based) algorithms and procedures that exploit human labelling and
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The University of Groningen is a research university with a global outlook, deeply rooted in Groningen, City of Talent. Quality has been our top priority for over four hundred years, and with
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quality of traditional HTR algorithms. We are looking for a highly motivated and qualified PhD student/researcher who will work towards developing new (machine learning and deep learning-based) algorithms
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uncomfortable or unpleasant. The results from human perception will then be used in the model to predict unpleasant in hand vibrations. An in hand discomfort model can be developed using machine learning
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the basis of a thesis leading to a PhD degree (Dr) at the University of Groningen. Organisation Founded in 1614, the University of Groningen enjoys an international reputation as a dynamic and innovative
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new (machine learning and deep learning-based) algorithms and procedures that exploit human labelling and machine-based clustering efficiently. Human labelling (from Dutch cultural heritage partners
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unpleasant in hand vibrations. An in hand discomfort model can be developed using machine learning approaches. Finally, we build an “in hand vibrations” discomfort standard. Organisation The University