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Field
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interdisciplinary team will develop a machine learning based monitoring system that leverages spoken language processing (SLP) and natural language processing (NLP) of speech recorded at home to calculate relapse
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neurocritical care research The Opportunity We are seeking a Research Fellow - Data Science professional with strong expertise in machine learning, deep learning and high-frequency physiological signal analysis
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in advanced signal processing techniques and good understanding of emerging machine learning methodologies used in NDE. You will work in close collaboration with project partners at the University
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-life environments. The Role: As Research Fellow on the COG-MHEAR project, you will have the opportunity to use your strong background in deep neural networks and multimodal hearing-aid signal processing
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of EU/ EEA countries and exemptions from the requirements: https://www.mn.uio.no/english/research/phd/regulations/regulations.html#toc8 Grade requirements: The norm is as follows: The average grade point
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software (Prism, Origin Pro, Matlab etc) A good understanding of appropriate statistical analysis techniques Qualifications Mandatory: PhD or equivalent in relevant field. Please Note: Appointment to
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model reliability and predictive confidence Publish high-quality scientific results in Tier-1 journals Job Requirements: A PhD degree in Mathematics, Computer Sciences, or related areas, with focus
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processing and machine learning, as well as, online control of assistive systems. The PhD position is located in Aalborg, and the candidate will be a member of Neurorehabilitation Systems group at the Health
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, the department hosts seven PhD candidates affiliated with various research groups and academic communities. The research group PrePast focuses on modern historical processes in the High North and the Arctic. A
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This is a theoretical/computational postdoctoral position for the prediction and development of point defects in two-dimensional materials for applications in quantum technologies. Project