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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
Knowledge in modeling and algorithms for large-scale ordinary differential equations (ODEs) and differential-algebraic equations (DAEs) Proficiency in a scientific programming language (e.g., C, C++, Fortran
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) experience in code development with parallel programming techniques using the message passing interface (MPI) library Proficiency in writing code with C, C++ and/or Python Ability to demonstrate strong written
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) Country Italy Type of Contract To be defined Job Status Full-time Hours Per Week To be defined Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related
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-scale scientific data. Publishing research in leading peer-reviewed journals and conferences. Researching and developing parallel/scalable uncertainty visualization algorithms using HPC resources
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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
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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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). 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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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description A postdoctoral position is available in the “Intracellular