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to evaluate pancreatic cancer pathology using human tissue specimens Assemble analysis pipelines using machine learning to process tissue data reproducibly and at scale Conduct analyses using programming
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mathematical foundations of data science, machine learning and/or artificial intelligence. Preference will be given to candidates studying either the application of data science/ML/AI to problems in
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students. Assist in grant proposal applications. Requirements: PhD in Mechanical Engineering, Machine Learning, Artificial Intelligence, Computational Mechanics, Material Science, Industrial Engineering, or
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opportunity to contribute to leading-edge research at the intersection of applied machine learning and clinical dental practice. As a member of our team, you will help translate contemporary data science
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; GIS; environmental data analysis; machine learning; numerical modelling; tracer experiments; dispersion and mixing. DESCRIPTION (topic, expectations, comments): We are seeking a researcher holding a PhD
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new machine learning methodologies that tackle unique computational problems in healthcare applications. We use large real-world complex datasets, including data extracted from electronic health records
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/or spatial genomics, computational biology, machine learning, bioinformatics, and systems neuroscience. Prior experience with deep learning applied to biological data is a plus. Practical experience
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). Applying advanced statistical and machine learning methods (e.g., predictive modelling, clustering, multivariate integration) to large-scale time series and sensor datasets. Contributing to the development
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the main deliverables to the consortium before 31 December 2028. In the remaining time of this position, the PhD candidate can write and finalize the thesis. Where to apply Website https
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opportunities for collaborations with machine learning and bioinformatics researchers in Computing and Information Systems, biostatisticians in Population and Global Health, big data research in genomics in