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drought early warning and monitoring system for large-scale river basins. The project will explore both data-driven and model-based approaches for drought predictions, paving the way for a continental high
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fields; • experience with large datasets, spatial and environmental analysis, and field work will be viewed favourably; • proficiency in R or similar scripting languages for data cleaning, analysis and
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of human cohorts” (65%, Proteomics Group) Ref. Number: 396_2026 PhD Position 3 “Image-based analysis of human cohorts” (65%, Lipidomics Group) Ref. Number: 397_2026 PhD Position 4 “Data Science” (100
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The Computer Vision Group is looking for an aspiring PhD to investigate multi-agentic AI, LLMs, and VLMs applied to agricultural sciences. Currently, established AI models often fail to generalize
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across multiple data modalities Manage HPC resources and job scheduling on NAISS Arrhenius CPU and GPU partitions Requirements To meet the entry requirements for doctoral studies, you must hold a Master’s
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London) has multiple, fully-funded PhD studentships available to accelerate its interdisciplinary research in the humanities, social sciences and digital sciences. Each scholarship is fully-funded
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further information Salary in position as PhD Research Fellow, position code 1017, 550 800 NOK. For exceptionally well qualified candidates a higher salary may be considered. By applying, the candidate
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are announcing the position as DDLS PhD student in Data driven evolution and biodiversity. Data driven evolution and biodiversity concerns research that takes advantage of the massive data streams offered by
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pangenomics of polyploids Project description This PhD project investigates how whole-genome duplication reshapes genome evolution using comparative pangenomics across multiple natural diploid–polyploid species
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Health emergencies, mass casualty events and disasters generate large volumes of operational, clinical and organisational data. However, these data are rarely synthesised into structured, analysable