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and other key actors, the project explores which governance models and policy instruments are most effective in achieving multiple objectives. The goal is to generate new knowledge about how forest
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specialization. A very good command of the English language is a key requirement. Documented knowledge and experience in machine learning is required; experience with natural language processing or with sequence
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of the following tasks using R/Python/bash scripting, such as genome assembly, SNP calling from re-sequencing data or RNA-seq data, and visualisation of high dimension dataset. Solid understanding of genetic
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redefinition. Architectural discourse has often relied on standardized bodily models that mask the diversity of lived, gendered, and capacitated experiences. In response, this project explores how a multiplicity
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the position Bioinformatic methods for single-cell metagenomic analysis Single-cell metagenomic sequencing (scMetaG) can provide maximum-resolution insights into complex microbial communities. However
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medical applications. Federated Bayesian learning offers a solution to those problems by allowing multiple participants to train machine learning models collaboratively, without sharing any data. Bayesian
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interactions with citizens. The position includes collaboration with researchers across multiple universities and international partners, and will involve empirical studies of AI use in public-sector