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Field
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problems in science and engineering on high-end parallel and distributed computing platforms. The employment duration is 3 years. Initially limited to 1.5 years, the employment relationship is automatically
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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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range of routine and complex digital intraoral and extraoral radiographs, including periapical, bitewing, panoramic, occlusal, and lateral images, and cone beam computed tomography scans. Aid dental
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, Interactive and Cognitive Systems, Distributed Systems, Parallel Computing, and Networks. The host team, DAISY, is a joint CNRS, Grenoble INP, and UGA research team handling research challenges
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22 Jan 2026 Job Information Organisation/Company SINGAPORE INSTITUTE OF TECHNOLOGY (SIT) Research Field Computer science Engineering Researcher Profile Recognised Researcher (R2) First Stage
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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | 22 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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of relevant experience in Linux systems administration or HPC systems engineering. Preferred Qualifications Demonstrated experience leading the design and deployment of HPC or large-scale distributed computing
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Program Director and distribute updated program policies · Plan, coordinate, order, obtain for new fellows; I9 compliance documentation; ID badges, Badge access, and parking at all training sites
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engineering; Formal methods, models, and languages; Interactive and cognitive systems; Distributed systems, parallel computing, and networks. The successful candidate will work closely with teams specializing
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distributed computing for EMT simulations. • Experience with software development in Python, C++, or other programming languages. • Familiarity with GPU acceleration of numerical solvers, parallel sparse