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learning models for segmenting and interpreting forest point clouds and rebuild them as real-time, incremental estimation systems. The work supports navigation, self-localization, and traversability work
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, including situations where some modalities are incomplete or unavailable. Exploring foundation-model and self-supervised learning approaches for extracting transferable representations from large-scale forest
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20th October 2026 Languages English English English The Department of Biology has a vacancy for a PhD Candidate in Modelling Marine Larval Dispersal and Spatial Population Genetics and Demography
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models ranging from baseline approaches to graph neural networks. You will also oversee the open release of project datasets, models, code and documentation. The successful candidate will join Oxford's
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preferred (Master’s degree or higher). Skills and Knowledge: Proficiency in programming, traffic simulation, statistical modeling, and machine learning/deep learning techniques. Excellent communication skills
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the microbiome acquired in early life influences immune development and intestinal health? Join an ERC Starting Grant project that combines advanced gut-on-a-chip technology, organoid models and omics approaches
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-) immunoprecipitations from neuronal cell models and brain tissue followed by quantitative LC-MS/MS, and you will run that workflow from end to end – from sample preparation to data analysis and interpretation. Candidate
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novel methodology for the analysis of single-cell (multi)-omics data by incorporating existing biological knowledge into machine learning models. You will join a collaborative and internationally-oriented
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English Join the University of Oslo for a PhD in Biomaterials! PhD Position – AI-Driven Multimodal Analysis and Predictive Modelling of Biomaterials Apply for this job See advertisement About the position
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, combining biodiversity surveys, animal movement data, landscape modelling and remote sensing to understand how trees within agricultural landscapes influence wildlife movement and landscape connectivity