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Field
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based on performance and available support. Environment and Opportunities The lab focuses on developing AI methods to improve patient diagnosis, prognosis, treatment response prediction, and treatment
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Intelligence (AI) approaches to quality control of coastal water level observations in a robust and time efficient way. The position is for one year, and it is renewable for an additional 9 months based
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, or related fields. Candidates are expected to have a demonstrable interest in bio-inspired neural networks and probabilistic approaches, and to have an excellent command of English. Needed
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networks are controlled, to develop predictive models of methane cycling in northern rivers. This postdoc position will focus on assessing how stream methane emissions are linked to permafrost thaw, using
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Conservation D. How plant cell shape and tissue structure help cells stick together E. DETERMINER - Determining appropriate monitoring frequency for phytoplankton F. Predicting bacterial protein expression
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RISC-V ISA. Your project will be on developing time-predictable RISC-V architectures to support multicore systems as a basis for real-time automotive functionalities. Responsibilities: Conduct research
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of neuroimaging data to predict subjective experiences and individual differences, as well as cognitive modeling of decision-making in both lab and realworld settings. Successful candidates will be supported in
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psychiatry on longitudinal multimodal data, to fit and validate prediction models. Perform quality control and imputation of genotype data from relevant datasets, including international and Norwegian samples
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health and translational medicine using a "bench-to-bedside" approach. By harmonising and analysing diverse biomedical data, while focusing on the secure data processing and predictive modelling, we aim
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capable of local shrinkage or expansion upon application of heat. The response should be predictable on the nm level from basic understanding of the processes involved during growth and heating. Key