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, monitoring, data acquisition and processing in MATLAB and cross-platform Python (Windows and Linux) and experience in integration of systems for synchronised acquisition and aggregation of data sources
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Linux environment is a plus, as is a good knowledge of brewing technology (and/or food technology). After an initial screening, suitable candidates will be invited for an interview, scheduled
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in C/C++ or Python. Knowledge of Linux (ubuntu), ROS 1 and/or 2, Gazebo and/or pybullet, Docker, git, Latex are a plus. Knowledge of SLAM, pose estimation, UWB, IMUs, VIO, LIO are a plus. Hands on
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bioinformatics programming and high-performance computing environments, including Python, R, Linux-based workflows, and HPC/cloud platforms for reproducible pipeline development. Evidence of strong scholarly
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computational scientific workflows. Experience with scientific programming (Python or similar) Experience working in Linux-based computational environments Documented experience with high-performance computing
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competence in programming with Python and working on Linux based platform is essential for this position, as is a background in either Mechanical Engineering, Material Science, Applied Physics and/or similar
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. Familiarity with Linux/Unix is an advantage. Where to apply Website https://emploi.cnrs.fr/Offres/Doctorant/UAR636-ALERUB-036/Default.aspx Requirements Research FieldEnvironmental scienceEducation LevelPhD
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IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | 13 days ago
/video processing, or multimodal data, · ability to read and implement research papers, · experience with the Git version control system, · experience with Linux operating systems and working in Bash
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IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | 16 days ago
/video processing, or multimodal data, · ability to read and implement research papers, · experience with the Git version control system, · experience with Linux operating systems and working in Bash
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computational scientific workflows. Experience with scientific programming (Python or similar) Experience working in Linux-based computational environments Documented experience with high-performance computing