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Summary: CBRAIN is a flexible Ruby on Rails framework for accessing and processing large amounts of data across a distributed network of High Performance Computing (HPC) and Cloud Computing
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: Steinberg Centre for Simulation and Interactive Learning (SCSIL) The Surgical Performance Enhancement and Robotics (SuPER) Centre in collaboration with Steinberg Centre for Simulation and
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proteomic and transcriptomic data. Analyze genotyping array, whole-genome sequencing and proteomic data from institutional and international cohorts on high-performance computing clusters. Work with
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Python and modern deep learning frameworks. ● Experience with High-performance Computing Infrastructure and GPU clusters. ● Strong research background in multimodal modeling, representation learning
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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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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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., Seurat, Scanpy, Cell Ranger). Familiarity with high-performance computing environments and job scheduling systems. Knowledge of Git/GitHub, version control, and reproducible research practices
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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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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