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for probabilistic unsupervised learning for structured biological data. The successful candidate will: Develop probabilistic factor models and scalable inference algorithms for structured biological (multi-view) high
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translational model based on patient-derived tumour organoids that reproduce the realistic microanatomy of the tumour. These organoids will be used for translational testing of nanotherapeutic activity
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northern Sweden create enormous opportunities and complex challenges. For Umeå University, conducting research about – and in the middle of – a society in transition is key. We also take pride in delivering
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mechanisms and model development to preclinical therapy testing, clinical readiness and patient-informed treatment priorities. To achieve this, POLARIS brings together expertise in leukodystrophy biology
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of software infrastructure to optimize data workflows Developing analytical methods to integrate different types of sequencing-based DNA data. Developing computational models for prognosis and treatment
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into the electromagnetic model for robust performance analysis? Information Antenna and RF systems play a pivotal role in society by providing a crucial enabling medical diagnostics, transportation, and communication in
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Sciences, Faculty of Medicine, University of Oslo. PhD Candidate in advanced immune competent liver models Apply for this job See advertisement About the position The Hybrid Technology Hub CoE (https
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gasification Experience with lab-scale reactor design, construction and operation Experience with experimental work Experience in Computational Fluid Dynamics (CFD) modelling Personal qualities In order to be
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they negotiate changes to their work and business models. Through ethnographic fieldwork you will research what practitioners value within the activity of making creative work, and how that changes
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for semantic search, interpretation summarisation, and interactive chatbot support for defining factual states and generating tax ruling applications. The project incorporates advanced NLP models, in-context