20 post-doc-image-processing Fellowship positions at UiT The Arctic University of Norway in Norway
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Stig Brøndbo 4th August 2025 Languages English Norsk Bokmål English English Faculty of Engineering Science and Technology PhD Fellow in signal processing and modelling in the seafood industry Apply
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questions related to the molecular regulation of autophagosome formation, using cell biological, genetic, and imaging-based approaches. The candidate will explore the function and regulation of proteins
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for clinical AI based on patient data from heterogeneous sources notably language/speech-based sources. The activity will focus on the development of a prototype implementation of early warning- and other AI
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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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of three topics: 1. Combining synthetic aperture radar (SAR) images with probabilistic weather prediction models to view and predict dynamic sea ice properties. 2. Using multi-frequency SAR, coupled with in
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) has a PhD position vacant in application for use of biodegradable materials in aquaculture - for applicants who wish to obtain the degree of Philosophiae Doctor (PhD). The position is attached
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in entrepreneurship, clinical process innovation, and industry collaboration. Contact Further information about the position and UiT is available by contacting: Professor Brita Elvevåg: phone +47
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is based on a previous qualifying position PhD Fellow, research assistant, or the like in such a way that the total time used for research training amounts to three years. We process personal data
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to three years. We process personal data given in an application or CV in accordance with the Personal Data Act (Offentleglova). According to the Personal Data Act information about the applicant may be
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of excellence. The main focus will be on developing novel voice and language-based natural language processing (NLP) methods for languages with less data than ideal for the development of cognitive tests