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languages (e.g. Python, C++, Java, Fortran or Matlab); has knowledge of advanced GNSS data processing and analysis methods, including visualization; has a scientific publication record in journals indexed in
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assembly. - Excellent English proficiency Skills: - Strong competence in the use of bioinformatic tools such as plink or bcftools is a must. - Excellent command of R and Python scripting is required
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and geoprocessing of environmental data; Competences in quantitative data analysis and statistical modelling applied to ecological studies; Experience in the use of programming languages such as Python
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problems, statistical learning and machine learning (machine learning, deep learning) - Knowledge of associated software development tools and environments: Python, PyTorch, Scikit-learn, Jax, Julia
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techniques. Training or demonstrated experience in remote sensing, spatial data collection, and thematic mapping. Proficiency in data analysis software (e.g., R, MATLAB, SPSS, Primer, Python). Experience with
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students enrolled in a graduate program at McGill University (preferably in Bioengineering, Mechanical Engineering, or Biological and Biomedical Engineering . Some experience with Python coding Knowledge
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or Python Life cycle assessment (LCA) Software related experience on system dynamics modelling, GIS, and energy simulations Research writing and publications Applicants must fulfill the eligibility and
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Proficient in documentation, technical writing, and reporting Experience in large-scale automation deployment project by Automation tools, proficiency in Ansible, Python, Bash shell and Terraform scripts
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. Proficiency in deep learning frameworks such as PyTorch or TensorFlow. Experience with ROS / ROS 2 for real-robot software integration. Proficiency in Python and C++, with good software engineering practices
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developing Python software and optimization workflows in Pyomo/PyROS is desired. This is a fixed-term position of up to 6 months and is inclusive of competitive salary and full-time benefits. The starting date