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on high-performance computing (HPC) facilities and adapt softwares to do so. Develop, benchmark, and troubleshoot new computational approaches, including implementing novel workflows, protocols, and
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- Knowledge of programming (Fortran, Python) - Previous experience with SIESTA will be a plus but it is not essential. - Previous experience with user-level High Performance Computing will be a plus but it is
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approaches, where data storage and processing occur simultaneously at the materials level, inspired by the operation of the brain. This includes research on unconventional computing paradigms, such as
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) Professional Experience: - Previous experience with SIESTA will be a plus but it is not essential. - Previous experience with user-level High Performance Computing will be a plus but it is not essential
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core facilities (including high-performance computing, cryo-EM, genomics, and metabolomics), and a culture of fearless, cross-disciplinary inquiry. The School of Life Sciences invites applications
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collaboration tasks within the group’s research line focused on the integration of high performance computing (HPC) strategies and methods for the scalable analysis and modeling of bioinformatics applications
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. Professional Experience: In Software Engineering and High Performance Computing. Experience in functions similar to those described will be valued, specifically in the development of research activities, both in
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their effect on process performance. • Communicate and disseminate research results through high-quality scientific channels, including peer-reviewed publications and presentations at international
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strongly recommended. • High Performance Computing. • Experience with High Throughput Calculations will be valued but it is not essential. • Previous knowledge of Density Functional Theory (DFT) and
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Bioinformatics and/or Computational Biology. b) OTHER REQUIREMENTS - Work experience related to bioinformatics. - Training related to the tasks to be performed (complementary academic qualifications, specialised