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utilization, or energy consumption of computing systems. • Ability to communicate technical material clearly and supervise team-based projects. Previous experience teaching in a large university-level course
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with high-performance computing (Slurm/PBS or equivalent) and/or cloud computing platforms. Working knowledge of at least one of: GWAS, Mendelian randomization, fine-mapping, colocalization, polygenic
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. Responsibilities: Build and optimize computational meshes for numerical simulations. Set up and validate simulation boundary conditions. Perform simulations using high-performance computing resources
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investments at the nexus where computing, data, and systems meet – particularly around AI and data science. Through training, data science solutions, and various mechanisms facilitating convergent research
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one-year temporary position in the McGill Engine Centre ( https://www.mcgill.ca/engine/ ), with the possibility of renewal. Full-time presence on site is required in a shared workspace. No work from
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MUMT 250: Music Perception and Cognition MUMT 306: Music & Audio Computing 1 MUMT 501: Digital Aud. Signal Processing MUPD 235: Music as a Profession 2 MUSR 692: Music Production Workshop MUTH 151
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learning and language models. ● Demonstrated experience analyzing large-scale health or biomedical datasets. ● Proficiency with Python, Git, and high-performance computing or GPU cluster
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learning and language models. ● Demonstrated experience analyzing large-scale health or biomedical datasets. ● Proficiency with Python, Git, and high-performance computing or GPU cluster
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and ongoing award administration. Oversee service delivery for research software, cloud-, and advanced research computing services to researchers. Ensure responsive, consistent, and high-quality
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-particle measurement techniques. Strong quantitative data-analysis and scientific computing skills. Ability to independently analyze and interpret complex experimental data. Ability to troubleshoot