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experience with scientific computing environments (Linux, HPC clusters) are wellcome. Background knowledge in adsorption phenomena, catalysis, or corrosion science is a plus, along with good communication
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, ability to critically discuss and present scientific results, and proficiency in English for oral and written communications. Experience with genome editing, bioinformatics (e.g. python, linux) and high
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on C++ and Python language. Administration level in Linux/Unix systems. Experience in HPC. Additional Knowledge and Professional Experience Good communication skills (verbal and written) in English, and
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Postdoctoral researcher (M/F). Modeling damage during earthquakes. Comparison with geophysical data.
candidate must demonstrate proven skills in digital development (C++, Fortran, Matlab, Python, or equivalent) and be proficient in the Linux environment. Additional knowledge in numerical analysis, continuous
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programming (e.g., Python) and working with Linux/Unix environments. Solid mathematical/statistical skills. Preferred/desired qualifications Experience in applying for ESA projects, Horizon Europe, and similar
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resident (mandatory), and able to work on-site at McGill downtown Montreal campus at least one day/week. Linux command line Familiar with (or able to quickly learn) Docker, containerization, client/server
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ideally be familiar with the UNIX environment (e.g., Linux). It will be desirable to have had previous experience in genetics, but not necessary. The applicants must be fluent in English, both oral and in
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computer networks is a plu Experience with Linux – Knows C++ and Python Knowledge of basic principles in one or more of the following: chemical synthesis, spectroscopy, engineering (nuclear, electrical
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technical skills and knowledge: Computational methods for data analysis Quantum Computing theory (e.g., QC algorithms) Practical Quantum Computing (e.g., Qiskit) Software development in Linux The following
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. Required competencies: Strong background in bioinformatics (e.g., R, Linux, Python). Experience working with large cohorts and high-dimensional data. Experience with microbiome analysis and/or GWAS