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: Machine Translation, Large Language Models, Automatic Speech Recognition, Automatic Speech Synthesis, Computer-Assisted Translation (CAT), Software Localisation, Terminology Extraction and Management
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Apply and key information This project is funded by: Department for the Economy (DfE) Summary This PhD project offers an exciting opportunity to develop next-generation biocomposites made from
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collaborate with experts in computational mechanics and machine learning. How to apply ?: Please submit a detailed CV, at least 2 recommendation letters or contact information of people who can recommend you, a
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. The position involves close collaboration with experts in cardiovascular simulation and Scientific Machine Learning. Your tasks: Development and comparison of data driven models for the prediction of stresses in
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The applicant must: hold a PhD in a relevant field (e.g. computer science, artificial intelligence, machine learning, computer vision, animal science, biology, veterinary medicine, or a related discipline) have
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descriptors, molecular simulations, and machine learning, this PhD project seeks to predict ion-exchange isotherm parameters directly from molecular properties. These predictions will be integrated
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Laszlo Bakó (molecular biology) and Torgeir R. Hvidsten (comparative genomics). The environment provides comprehensive support for large‑scale multi‑omic data generation/analysis and transformation
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related field, and a strong interest in biomedical applications. Experience in machine learning, statistics, or high-dimensional biological data analysis is advantageous. Ideal candidates are curious
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and the terms of the research grant when extending an offer. Completion of PhD in Data Science, Computer Science, Mathematics, or other discipline aligned with CDS faculty research by the start date
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-scale research facilities (e.g. DESY, ESRF), including coordination and setup of experiments Development of data workflows and analysis strategies (in collaboration with our machine learning team