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journals and conferences. Researching and developing parallel/scalable uncertainty visualization algorithms using HPC resources. Collaboration with domain scientists for demonstration and validation
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parallel programming concepts). Experience with open-science practices (version control, documented pipelines, FAIR-aligned releases). All candidates and projects will have to undergo a check versus national
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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | 6 days ago
Status Full-time Hours Per Week 35 Offer Starting Date 23 Feb 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Reference Number Fellow_BI/FCT_Proj2025/i3S
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Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Horizon Europe Reference Number 2026-R0183 Is the Job related to staff position within a Research Infrastructure
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investigates how exercise and stress signaling regulate muscle function and healthy aging through an integrated research program combining mechanistic studies in Drosophila melanogaster with human clinical
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thick and strongly scattering samples. Experience in high-performance computing, parallel programming, or GPU-accelerated computation for large-scale 3D reconstruction. Experience applying machine
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). Expertise in data and model parallelisms for distributed training on large GPU-based machines is essential. Candidates with experience using diffusion-based or other generative AI methods as
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Researcher (R1) Application Deadline 20 Feb 2026 - 00:00 (UTC) Country Singapore Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU
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datasets (e.g. video, acoustics, clinical records) for predictive modelling and decision support. Proficiency in programming languages such as Python (and/or Java, C/C++), with hands-on experience using deep
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expected to design and drive independent research projects, contribute original ideas for new research directions and funding applications, and analyse complex datasets using programming tools such as Python