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material science. The candidate will participate in in vivo experiments to evaluate different debridement tools for infected implants and subsequently analysis. Throughout the in‑vivo phase you will develop
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for appointment. Good knowledge of programming and data analysis using Fortran, Matlab, Python, or similar programming languages. Experience in using and developing models to simulate natural systems. Knowledge
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pedagogical competency in the course of their fellowship period within the duty component of 25 %. No one can be appointed for more than one Postdoctoral Research Fellowship at the University of Oslo. Project
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knowledge for precision medicine in psychiatry, building on advanced statistical methods for analysis of large-scale human genetic and neuroimaging data, to better understand how biological, psychological
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Fellowship period at the University of Oslo. The fellowship period is 3 years. This position is part of the research project “Numerical Analysis of Stochastic TRANsport” (NASTRAN), funded by the Research
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five years. Documented potential for acquisition of external funding. Pedagogical qualifications and teaching and supervision experience at all levels will be an important factor in the evaluation
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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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. The applicant's estimated academic and personal ability to complete the project within the time frame The applicant's ability to complete research training Methodological skills in textual/cultural analysis and/or
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experiments and electron microscopy analysis in collaboration with Prof D. Healy and Prof. S. Piazolo. The postholder will be en-couraged to develop a leadership role within the project, present internal
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, recommender technology, content production and analysis, content interaction and availability, and Norwegian language technology. The goal is to develop responsible technological solutions to societal