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collaboration in optimising data analysis algorithms for the raw detector data, including improving position reconstruction and pulse-shape discrimination algorithms which can be implemented on in the front-end
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scale healthcare data analysis for development of precision medicine approaches. The researcher hired for this postdoctoral fellow position will work with the Centre’s datasets, analytical methodology
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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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at the University of Oslo. The main goal is to develop tools and knowledge for precision medicine in psychiatry, building on advanced statistical methods for analysis of large-scale human genetic and neuroimaging
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; mathematical modelling of cancer; probabilistic modelling and Bayesian inference, stochastic algorithms and simulation-based inference; causal inference and time-to-event analysis; and statistical machine
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medicine in psychiatry, building on advanced statistical methods for analysis of large-scale human genetic and neuroimaging data, to better understand how biological, psychological, and environmental factors
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approaches from STS and/or innovation studies such as valuation studies or care studies will be considered an advantage. Experience with qualitative document-analysis, ethnography and/or interview studies will
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collaboration with the theorists involved. The postdoc will construct and use 3D printed model porous media. The analysis will entail extensive use of image analysis techniques such as Particle Image
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also count in the assessment of the applicants: optogenetics, chemogenetics, computational and statistical methods for analysis; rodent behaviour, histology methods, sleep scoring, neurodevelopment as
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the following will also count in the assessment of the applicants: optogenetics, chemogenetics, computational and statistical methods for analysis; rodent behaviour, histology methods, sleep scoring