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[Eshmuminov et al. Nat. Biotechnol. 2020] and the first clinical transplantation of a liver treated and recovered in a perfusion machine [Clavien et al. Nat. Biotechnol. 2022]. In parallel, the lab has
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released models Make evaluations run quickly and at scale: parallel execution on Alps, efficient use of inference backends, caching, and result tracking Reduce mismatch between evaluations during
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/aarch64 platforms Familiarity with HPC networking and communication stacks: Slingshot, libfabric, NCCL and its debugging Experience with parallel filesystems (e.g. Lustre) and storage performance tuning
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experience operating Linux systems in production environments Experience automating repetitive operational tasks Experience with shell scripting (Bash) and programming in at least one language such as
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programming skills, and prior experience training and evaluating neural network models (e.g. in PyTorch). Familiarity with biomechanics or finite-element modelling is an advantage. Background
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will be conducted in parallel with a sister study in the Canadian Rocky Mountains (a similar position is being advertised at McGill University – see here , Students are welcome to apply to both if they