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methodology for analysing long-term spatially structured data sets within a joint species distribution modelling framework. For more information on REC, please see https://www2.helsinki.fi/en/researchgroups
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, are available and encouraged. Candidates should have a doctoral degree in ecological statistics, statistics, or similar area, and previous experience in working with hierarchical Bayesian models and Markov chain
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, the appointee’s work will cover some of the following areas: Development of an isotope version of the process-based CH4 model and parameter optimization for different wetland types. Coupling the updated CH4 model
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(FIMM) , University of Helsinki, is currently seeking a highly-motivated postdoctoral researcher to join our interdisciplinary team. Project overview This project aims to develop machine learning models
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immune-system related diseases such as immunodeficiency and cancer. We use a wide range of techniques such as mouse models, tumor models, in vivo immune cell migration and other functional assays, flow
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metagenomics assembly” funded by the Research Council of Finland in the research group of University Lecturer Leena Salmela. We develop models, algorithms and data structures for high throughput sequencing data
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project CONFSTAT – Conformally invariant and near critical models in statistical field theory. The work of the postdoctoral researcher will focus on studying conformally invariant models of statistical
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and/or qualifications A completed doctoral degree in any relevant discipline, with a documented publication record considered a significant merit Scientific competence in computational biology
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aims to conduct should contribute to (at least one of) the mentioned research themes and provide novel scientific knowledge to the field of studies in migration and racism. The thematic area of
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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