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the research group of Professor Klaus Nordhausen in the project “Signal recovery in noisy spatial data”. The research group develops modern and efficient multivariate statistical methods tailored
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theoretical background and a degree in cell and molecular biology (or similar field) and preferably some practical experience in cell culture and/or functional genomics methods. For the Doctoral Researcher
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empirical, experimental and theoretical methods, together with world-class administrative data on individuals and firms. Some of the work is done in collaboration with revenue authorities, also in African
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using unique novel mouse models, spatial technologies and analytical methods. Postdoctoral Researcher in Functional Cancer Microbiome through the NORPOD program NORPOD is a collaborative postdoctoral
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, or equivalent. They will have training and/or experience in ethnography, qualitative analysis, and the use of non-textual/sensory methods. Period following the completion of doctoral degree must not exceed three
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. We develop machine learning methods tailored for high-dimensional, multimodal biological data, with applications ranging from single-cell genomics to real-world clinical datasets. We are active
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, calibration, and the development of analysis tools and software. Our key focus areas are the physics of jets, top quarks, and EWSB, including the development of novel machine-learning methods for high-energy
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disposal strategies and sustainable resource management practices. The project also has synergy the ongoing EURATOM EURAD2 RAMPEC work package, and it is expected that some of the methods developed in HiFi
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group, established in 2018 at the University of Oslo, has recently expanded to the University of Helsinki. The group specializes in developing computational methods to understand the regulatory mechanisms
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methods to understand the regulatory mechanisms driving cancer heterogeneity and progression by integrating genomic data into genome-wide regulatory networks. Current projects include (i) modeling distal