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Field
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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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(or equivalent) on their master’s degree in order to be admitted to the PhD programme. The grade point average also applies to 300 ECTS points integrated five-year master’s degrees, in which all courses are to be
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, electrical & electronic engineering, or equivalent. Background knowledge in signal representation/processing, visual data compression, and data-driven and machine learning/analysis. Prior research experience
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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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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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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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collaborative transdisciplinary PhD cohort Co-develop energy literacy and communication projects Collaborate with academic, government, and community partners to co-create research directions Mentor graduate and
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workshops, public talks, and community engagement activities Conduct a meta-study on collaborative transdisciplinary PhD cohort Co-develop energy literacy and communication projects Collaborate with academic
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-study on collaborative transdisciplinary PhD cohort Co-develop energy literacy and communication projects Collaborate with academic, government, and community partners to co-create research directions
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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