8 condition-monitoring-machine-learning Postdoctoral positions at University of Oslo in Norway
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data, MRI data, and other types of data. Contribute to projects at LCBC with data analysis, development, and implementation of advanced machine learning models. Write and publish scientific articles
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the SFF Integreat, The Norwegian Centre for Knowledge-driven Machine Learning (ML) , a centre of excellence funded by RCN and in operation until 2033. The project PI and team are also in close collaboration
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. Your main tasks will be Develop and apply machine learning techniques and statistical analyses, including novel methodology for analysis of complex polygenic traits and prediction tools for precision
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Develop and apply machine learning techniques and statistical analyses, including digital twin methodology, to fit and validate prediction model. Perform quality control and imputation of genotype and
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studies. Proficiency in relevant computational tools and statistical methods. Experience with machine learning in large datasets. Interest and motivation to work in a multidisciplinary team. Ability to work
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offers a unique platform for studying sleep and circuit-level maturation in vivo, with rodent models of sleep deprivation, developmental sleep monitoring, and electrophysiology recordings. The Kim group
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recruitments. The Boccara group offers a unique platform for studying sleep and circuit-level maturation in vivo, with rodent models of sleep deprivation, developmental sleep monitoring, and electrophysiology
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the postdoctoral fellow should acquire. UiO is responsible for following up on the career plan and ensuring that the postdoctoral fellow has access to career guidance throughout the postdoctoral term. A PhD position