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                science, mathematical modelling, data science, transport behaviour, or related fields? Then this PhD position might be the right for you. Ensuring sustainable mobility in dense urban areas is a big challenge faced by 
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                learns auditory information. Methodologically, the project will explore the integration of information-theoretic decompositions, deep neural architectures, and large language models (LLMs) as powerful 
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                the ERC Starting Grant research project “Exploiting Nanopore sequencing to discover what microbes eat (NanoEat)” with the aim to combine state-of-the-art metagenome sequencing with state-of-the-art data 
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                scholarship as of April 1, 2026, or as agreed. Be part of a large-scale international project We are looking for a talented and motivated PhD student for the EPHEMERAL research project. EPHEMERAL 
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                25 Oct 2025 Job Information Organisation/Company Aalborg Universitet Department The Technical Faculty of IT and Design, Department of Computer Science, Section for DATA Research Field 
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                Job Description The eScience Center at the University of Southern Denmark (SDU) develops and operates large-scale IT infrastructure dedicated to research in all fields. The center is a leading 
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                sensing and responding to the chemical landscape surrounding them as well as the chemical signals inside of them. This project is devoted to gather large data sets to investigate links in olfactory receptor 
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                to vastly improve our ability to recover microbial genomes from metagenomes. Specifically, we aim to take advantage of the vast amount of high-quality long-read data that is readily obtainable using 
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                . The position The successful candidate is expected to work closely with the LoCiS PI, Professor Rubina Raja, on a number of tasks, including: supporting large research/publication projects (including copyediting 
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                Experience with writing scientific publications Experience in working with contaminants like PFAS, PCBs and mercury, fatty acids, stable isotopes and modelling in R A talent for working with large data sets