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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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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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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
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the applicants, in the disciplinary area of the tender, preferably in the scientific areas of Computer Security or Parallel and Distributed Computing and its adequacy to the category of Assistant Professor
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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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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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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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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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to accelerate discovery through advanced computing, artificial intelligence, and data-driven science, supported by state-of-the-art cyberinfrastructure (CI) systems, tools, specialized software, and applications