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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | 5 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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About the Opportunity Job Summary Reporting to the Assistant Vice President, Individual Giving, the Executive Director of Major Gifts, Gift Planning will develop a broad strategic plan for
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. Connections working at Dana-Farber Cancer Institute More Jobs from This Employer https://main.hercjobs.org/jobs/22062766/program-administrator-smith-lab Return to Search Results
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-aware learning methods with domain decomposition techniques, enabling parallel training and efficient GPU-supported implementation. Your tasks: Development of physics-aware ML models for 3D blood-flow
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following table(s) for the salary scale(s) for this position https://www.ucop.edu/academic-personnel-programs/_files/2025-26/policy-covered-october-2025-scales/t1.pdf The base salary range, from the salary
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, computer science, simulation science with a strong background in applied mathematics Excellent programming skills (Python, C/C++) Good experience in machine learning and parallel computing Good organisational skills
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IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | 27 days ago
operates the first Czech quantum computer named VLQ. https://www.it4i.cz/ Activity description: development of a Python application with a graphical interface, compilation of parallel applications and
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, Wellness Programs, Educational Assistance, Relocation Assistance, and Employee Discounts. We are not accepting applications for this job through MathJobs.Org right now. Please apply at https://jobs.ornl.gov
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Demonstrated research experience with HPC, AI/ML and/or distributed systems techniques. Proficiency in programming languages such as Python, C++, or similar, as well as experience with HPC environments and
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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