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and functional diagnostic methods. These methods are used in everything from experimental research to clinical studies on patients and large-scale epidemiological studies on volunteers. In
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-throughput sequencing of genomes and biomes, continuous recording of video and audio in the wild, high-throughput imaging of biological specimens, and large-scale remote monitoring of organisms or habitats
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framework that integrates multiscale molecular dynamics (MD), AI and machine learning (ML) approaches, that together with biophysical characterisation techniques will advance the current state of lipid
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and advanced causal inference methods to large-scale multi-omics datasets, national health registers, and other comprehensive health-related data sources. Duties The doctoral position is intended
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large-scale remote monitoring of organisms or habitats. The project focuses on trying to disentangle population structure among archaic and modern humans over time. The project will investigate
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or predictive modelling of pathogen biology or host-microbe systems for which multidimensional, genome-scale experimental data are now available or it may use population-scale genetic, clinical, or public health
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have a strong focus on computational analysis or predictive modelling of pathogen biology or host-microbe systems for which multidimensional, genome-scale experimental data are now available or it may
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algorithms to detect complex structural variants in humans using long DNA sequencing reads. A structural variant (SV) is a large-scale alteration in the genome that involves rearranged, deleted, or inserted
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the professional ability to work independently on their specific project over time On a larger scale, Karolinska Institutet is one of the world’s leading medical universities, with the vision to provide better
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molecular biology project is to combine image processing and AI to develop a framework for large scale registration, and interactive visualization and analysis of 4 different types of in situ image