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, or SyCL/OpenCL. Hands-on experience with machine learning, including end-to-end training, tuning, and evaluation of at least one class of models. Working understanding of common machine learning model
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Postdoctoral Positions for Computational Genomics, Cancer Genetics, and Translational Cancer Biology
mechanism-driven AI and agentic AI frameworks (iGenSig-AI, G2K) that integrate biological knowledge with cutting-edge machine learning to transform omics data into actionable therapeutic insights
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and machine learning. Dr. Liu's research interests lie in modeling the rapidly-accumulating big data (e.g., muti-omics) in biology and medicine for precision medicine via a variety of statistical and
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multimodal generative AI for music/audio. Check out some of our recent projects here: https://dorienherremans.com/biblio (including work on models like Mustango, SonicMaster and other generative systems
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for 10-12 weeks. Responsibilities: Collect and organize different datasets. Derive summary statistics of those datasets. Help with the implementation of machine learning models. Conduct literature
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] Subject Areas: mathematical modeling, statistics, machine learning, data-driven modeling, dynamical systems, optimization Appl Deadline: 2026/04/01 04:59 AM UnitedKingdomTime (posted 2026/02/19 05:00 AM
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the leadership of Principal Investigator Dr Andrew Siemion. Listen's interdisciplinary research has synergies with many of the department's research priorities, including exoplanet studies, machine learning
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to create interactive learning experiences. Career Readiness Competencies Take initiative to learn new tools, systems, or procedures on the job. Present ideas or updates in a clear and organized manner. Ask
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Knowledge, Skills, and Abilities: Hands-on experience performing FEFF calculations and data preprocessing for machine learning applications. Practical experience developing and training models using PyTorch
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Sorbonne Université SIS (Sciences, Ingénierie, Santé) | Paris 15, le de France | France | 16 days ago
collaboration with L. Bonati at IIT Genova, who developed the library mlcolvar, https://github.com/luigibonati/mlcolvar ). 2) Compare the data-science dimensional reduction approaches above, with machine learning