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Field
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PhD Studentship: Distributed and Lightweight Large Language Models for Aerial 6G Spectrum Management
generation of wireless communication (6G) to extend network coverage, supporting diverse data-intensive applications such as immersive extended reality and autonomous systems. However, aerial 6G networks will
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This is a four-year (1+3 MRes/PhD) studentship funded through the Cambridge EPSRC Centre for Doctoral Training in Future Infrastructure and Built Environment: Unlocking Net Zero (FIBE3 CDT). Further
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the goal of building a multiscale foundation of knowledge that is directly relevant for understanding complex human diseases. This project is part of the TRANSCEND Doctoral Network (https://biomed.au.dk
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the full benefit from the network training As secondments and events are foreseen, applicants must be ready to travel Applicants must be eligible to enroll on a PhD program at TU Dresden (see https://tu
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process Applications will be reviewed on a rolling basis until the position is filled. Additional comments Project Overview Cells sense, integrate, and respond to dynamic stimuli through complex signaling
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in accordance with the applicable national regulations. Please find additional information in the Information package for Marie Curie fellows in doctoral networks (https://op.europa.eu/s/z831
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simulation of technical systems Interest in practical work with catalysts, laboratory setups and pilot-scale plants Ability to analyse complex interrelationships and work methodically Good written and spoken
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their applications. Using machine learning and related tools to enhance quantum memory advantages in stochastic simulation. Using advanced tensor network techniques to enhance the modelling of complex, memoryful open
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volunteers and analysing complex hormonal and physiological datasets. You will work with collaborators across the training network including a secondment to a specialist primary aldosteronism centre in Munich
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conducting a study with healthy volunteers and analysing complex hormonal and physiological datasets. You will work with collaborators across the training network including a secondment to a specialist primary