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Field
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. Familiarity with statistical modelling, machine learning and deep-learning Additional information: We offer: 🌐The opportunity to work with our state-of-the-art HPC infrastructure and to join a vibrant network
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. Preliminary exposure to machine/deep learning, statistical modelling or generative AI. Application process: Interested candidates are invited to apply via the PHYNEST online platform by submitting a full CV, a
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projects using NGS techniques applied to oncology. The candidate will mainly carry out the following tasks: • Analysis of high-throughput omics data with state of the art methods including machine learning
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FieldBiological sciencesEducation LevelPhD or equivalent Specific Requirements PhD in Physics, Computational Biology, Bioinformatics, or equivalent. Knowledge of biophysics, statistical physics, machine learning
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the project ‘MultiLearn: A multimodal approach to language learning: a window into the linguistic skills of children with neurodevelopmental disorders‘. The project is led by researchers Alfonso Igualada and
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working model that combines remote working with work on-site, according to organizational needs and the nature of the tasks involved. About the UOC A leader in e-learning, our pioneering university is a
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Offer Description We are seeking a PhD student to develop the project ‘MultiLearn: A multimodal approach to language learning: a window into the linguistic skills of children with neurodevelopmental
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, or a related field. Proven experience in machine learning, deep learning, generative AI and data mining. Strong programming skills (e.g., Python, R, MATLAB, or similar). Experience with data
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Networks and Services (PONS) Research Unit (https://www.cttc.cat/packet-optical-networks-and-services-pons/ ) is looking for a PhD candidate to actively participate in the team activities in the framework