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Field
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computing architecture and/or system software such as massively parallel computing, big data infrastructure, large-scale data system, or system software in general has been considered as important
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into agent-based models. Familiarity with parallel computing and cloud-based simulation environments. Knowledge of specific domains such as epidemiology or social sciences. Familiarity with web-scraping and
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research computing, systems engineering, or a closely related technical field supporting research environments Hands-on experience managing HPC clusters, job schedulers, and parallel file systems  PREFERRED
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(AWS, Azure/GCP) Experience in open source software development. Knowledge of GPU-based computing, including multi-gpu/multi-node parallelization techniques will be valued. Fluency in spoken and written
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for designing, deploying, and maintaining advanced research computing infrastructure and services in support of the university’s research mission. This role collaborates closely with faculty, research staff, and
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through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The Ph.D candidate will join a group of
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science such as computational complexity, algorithms, data structures, logic in computer science and AI, semantics, theory of programming, learning theory, parallel algorithms or quantum computing Research
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Stanford University / SLAC National Accelerator Laboratory | Menlo Park, California | United States | about 2 months ago
tasks in support of the research program, frequently interacting with the laboratory’s scientific community. To be successful in this position, you will bring: A Ph.D. in physics or a related discipline
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- 12:00 (UTC) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Horizon 2020 Is the Job related to staff position within a Research
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this multidisciplinary team, the candidate will have access to state-of-the-art technologies (massive parallel sequencing, mass spectrometry-based proteomics, high-performance computing infrastructure and data science