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, including single-cell RNA sequencing, spatial transcriptomics, or computational immunology using R or Python, is a plus but not required. Excellent organizational skills, attention to detail, and a
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development experience using Python, ROS2 and software engineering techniques. Extensive knowledge of ML, DL and RL tools, theory and applications. Before applying, please note that to work at McGill University
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relevant discipline and possess sufficient specialist knowledge in the discipline. You should be proficient in Python or R with experience in data science libraries, advanced NLP and LLM techniques and
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communication, or signal processing. Proficiency in programming languages like Python, MATLAB, or C++, and experience with AI/ML frameworks like TensorFlow, PyTorch, or scikit-learn. A proven track record of
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. The candidate will have hands-on experience with Edge AI and embedded systems security, as well as a solid grounding in AI security and Trustworthy AI. They will be proficient in Python and ideally familiar with
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data to calculate displacement Coding skills in Matlab/Python for processing/analysing data measured in the field Experience with working with public bodies to get access to historic bridge data
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representing transcription reaction networks, enzyme kinetics, and transport phenomena. Simulate mRNA production in enzymatic tubular reactors using MATLAB, Python, or related computational tools. Prepare
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experience in artificial intelligence, software engineering, automatic testing, program synthesis Excellent background and experience in programming language, especially python Good communication and report
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Documenting and testing codes Improving upon existing machine learning and numerical models Your qualifications: Excellent Python programming skills, Matlab and C++ experience is a plus Interest in Space
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) Experience with deep-learning based image analysis and programming languages such as Python and MATLAB (Advantageous) Highly motivated and willing to learn Salary and benefits are commensurable to educational