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on combining innovative technologies such as remote monitoring, large language models, machine learning, blockchain, and eco-accounting to enhance the efficiency, security, and sustainability of e-bike charging
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Erasmus MC (University Medical Center Rotterdam); Published 3 Nov ’25 | Netherlands | about 1 month ago
international collaborations, including the Observational Health Data Sciences and Informatics (OHDSI) initiative, a global consortium dedicated to harnessing the value of health data via large-scale analytics
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I specialise in the numerical modelling of high-energy particle collisions , such as those occurring at the Large Hadron Collider. Accordingly, most projects I offer straddle the intersection
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. This project will use large-scale metagenomic mining to uncover novel phage-host associations and identify phage-encoded enzymes, such as endolysins, with antibacterial activity. By integrating evolutionary
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aims to develop data-efficient and reliable training strategies for vision foundation models, reducing the need for large datasets and improving robustness. The project will explore strategies related
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) for analyzing large data sets Place of work: Umeå Forms for funding or employment: Employment as PhD student (4 years of education) Starting date: The preferred starting date is 1 May 2026, but flexible according
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the theoretical developments in computation argumentation (CA), information retrieval (IR), and natural language processing (NLP) using recent advances in large language models (LLMs). The candidate is expected
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layers, using transport and optical techniques to measure the relevant properties. They will have the opportunity to work with two large-scale facilities which the research division is responsible
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able to work with very large data and have the creativity and curiosity to work with network measures and statistics. You may also be an expert on grounded computational social science: combining large
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for these architectures remains a key challenge. This project will explore how reconfigurable/spatial computing devices can be integrated into large-scale heterogeneous infrastructures, which include CPUs, GPUs, DPUs, and