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Field
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Modelling, Applied Statistics, Linguistics, Data Analysis, Large Language Models, Machine Learning. Start date: 1st October 2026 Deadline: 30th April Duration: 36 months Funding: Funded Funding towards
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research in one of the Department's key research areas: (i) Artificial Intelligence and Machine Learning; (ii) Big Data Analytics and Management; (iii) Computer Vision and Pattern Recognition; and (iv
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and mapping, light fields, extended reality (XR) technologies, sim-to-real, synthetic data generation, and advanced computer vision and machine learning techniques. In addition, the group works on
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statistical modelling of high-dimensional data, e.g. penalised model selection and machine learning. Demonstrable understanding of RNAseq and gene expression analysis. Experience/skills handling and securely
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Science, Machine Learning, Finance, FinTech, Economics, or a related field. Candidates should demonstrate knowledge of Large Language Models, generative AI, and machine learning, with interest in financial
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the "Machine Learning and Gene Regulation" team led by William Ritchie, specializing in bioinformatics and post-transcriptional regulation. The scientific environment at the IGH — international seminars, journal
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precision medicine based on gene sequencing time series data. Large data sets come with significant computational challenges. Tremendous algorithmic progress has been made in machine learning and related
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and quantum solid state physics is absolutely essential Good computer skills are a plus We offer Your job with impact: Become part of ETH Zurich, which not only supports your professional development
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student in this project, you will contribute to the development of new models and methods in machine learning for D-MIMO integrated sensing. This includes working with large amounts of data generated by a
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complex interaction patterns that may carry important biological information. By integrating deep learning, genome-wide simulations, functional genomics, and large-scale biobank data, AI:GENOMIX aims