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/ External / View Profile U of T Employee Sign In More Filter Options: Campus and Job Category Loading... Clear Create Alert Apply now » Sessional Lecturer - CSC367H1S - Parallel Programming Date
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position comprises research and teaching at bachelor's, master's and doctoral level in computer science, primarily in operating systems, compiler construction, systems programming, and parallel and
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statistical mechanical theory to analyze the simulation results Basic understanding of parallel application development techniques (parallel programming models, algorithms, and software) Preferred
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, 2008) Required knowledge Be familiar with Big Data technologies (e.g. Apache Spark, Kafka) Have prior knowledge on or experience in parallel processing or data stream/IoT Have strong programming skills
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: Experience with CUDA programming; Experience programming distributed systems; Experience with parallel and distributed File Systems (e.g., Lustre, GPFS, Ceph) development. Advanced experience with high
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computer science or a related discipline. Good knowledge of agentic AI/AI workflows, parallel computing, algorithms, and system performance analysis and optimization. Proficiency in programming languages
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and cloud computing. Documented ability to teach operating systems. Documented ability to teach compiler construction. Knowledge of parallel programming. Experience of software development or cloud
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Inria, the French national research institute for the digital sciences | Talence, Aquitaine | France | 9 days ago
core of the project is the exploration of leveraging task-based parallel and distributed programming techniques in the DDF-pipeline software components with the aim to accelerate such processing on high
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tensor network algorithm development and application. Competency with common scientific programming languages such as C++, Python, and/or Julia and version control systems. Experience in parallel
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. Enforce security best practices including node hardening, kernel patching, and compliance across all systems. Manage parallel file systems such as Lustre, GPFS, Weka, or Vast, including performance