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Field
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domain and will be involved in research and innovation projects in the field of HPC computing. The planned activities include research and development of applications on Linux operating systems and the use
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environments. Experience with parallel computing environments, HPC in a Linux environment. Experience with surrogate modeling. Experience with data analytics techniques. Familiarity with C++ and GPU programming
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IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | about 1 month ago
Computing systems, o work in Linux environment and CLI, o code containerisation, o proficiency with git, o Ph.D. in computer science or mathematics, o proven scientific record in AI topics
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University of Massachusetts Medical School | Worcester, Massachusetts | United States | about 2 months ago
; proficient with Unix/Linux. Experience with deep learning, statistical modeling, or AI applications to biological data. Familiarity with transcriptomic technologies, ideally single‑cell RNA‑seq or long‑read
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experience in working with Linux HPCs · Experience in applying machine learning methods to genomics data analysis · Experience in navigating public databases and genomics data repositories
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on HPC clusters and on Linux/Unix environments. Previous experience with methods as FoldX, Rosetta, Molecular Dynamics Simulations, EVE and analyses of disease-related databases such as ClinVar or COSMIC
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Analytics, Geography, Computer Science or related field Linux arcGIS Scripting or programming experience (e.g., Python) Experience with imagery data Google suite Special Instructions: If you are selected as a
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meteorological datasets. Good programming skills in languages such as Python, MATLAB or R. Familiarity with UNIX/LINUX. High level analytical capability. Ability to communicate complex information clearly. Ability
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frameworks (preferably Pytorch) Use of Linux GPU servers via command line Written and spoken scientific English It would be a plus to have familiarity with: GIS and remote sensing Internal Application form(s
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, Python, Mplus, or similar) - Familiarity with big data, Linux systems, and remote computing clusters - Experience with genome-wide statistical genetics approaches (e.g., GWAS, genetic correlations, PGS