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, GNSS positioning is highly susceptible to errors from atmospheric distortions, multipath effects, and receiver noise. Recent advances in deep learning have shown that data-driven pseudorange correction
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, various types of leave, and options for sports and cultural activities . You can also tailor your employment conditions through our Terms of Employment Options Model. In this way, we encourage you to keep
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Modelling of Weather Impacts: Build machine learning models that analyse these integrated data streams to identify early precursors of weather-induced disruptions. The goal is to forecast turbulence zones
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, encompassing advanced geospatial analysis, remote sensing methods, atmospheric transport modelling, and epidemiological data integration. The researcher will also receive guidance in handling large datasets
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PhD Studentship: Distributed and Lightweight Large Language Models for Aerial 6G Spectrum Management
-latency, and scalable operation in aerial 6G networks. In this regard, Large Language Models (LLMs) have recently emerged as a key technology to achieve adaptive 6G spectrum management. The core idea of LLM
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. Multiscale simulations of the downstream expansion behaviour of the engine exhaust plume for different atmospheric layers. Definition of suitable interfaces to process data for the climate models. Expected
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research. The student will work closely with colleagues in the topical area of Atmospheric and Climate Physics (ACP). The successful candidate will have opportunities to present their work at international
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pilots to real-world systems. The overarching aim is to deliver a scalable approach, pairing shared “aggregator” models with household-specific “client” models that exchange knowledge while keeping data
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We are looking for 4 highly motivated PhD students to join our research team for a project focused on battery modelling, state estimation, fault diagnosis and control. Information Batteries
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the MicroHH atmospheric model. Analysis of plume dynamics and NOx chemistry in the high-resolution simulations. Develop and refine data-driven methods for emission quantification. Apply your methods to real