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Field
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development skills Model deployment (e.g., ONNX, TensorRT) Edge computing or embedded vision systems (e.g., NVIDIA Jetson Nano) Real-time processing and GPU acceleration Experience working on industry R&D
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astrophysical free boundaries. Responsibilities include running high-resolution GPU-accelerated simulations on exascale computing systems, developing and applying geometric measure theory tools to quantify
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distributed computing for EMT simulations. • Experience with software development in Python, C++, or other programming languages. • Familiarity with GPU acceleration of numerical solvers, parallel sparse
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scientific computing. You are proficient in several languages (Python, C/C++, or Fortran), with extensive knowledge in AI/ML and parallel programming (GPU, multi-threading, etc.). You have strong software
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projects to the Tier 2 supercomputer Bede (32 IBM Power 9 dual-CPU nodes, each with 4 NVIDIA V100 GPUs and high performance interconnect). The Bourne-Worster group is also well-provisioned with
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algebra methods targeting large-scale HPC systems. Optimization of linear algebra libraries for modern architectures (e.g., GPUs). Exploration of linear algebra methods in computational physics applications
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modeling, or ordinary/stochastic differential equations. Experience in computational, statistical, or machine learning method development in any discipline. Experience in GPU computing frameworks (e.g
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) and reproducible research practices Desirable criteria Experience working with generative models or large language models Experience with large scale GPU-based model training and cloud computing
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Experience working with generative models or large language models Experience with large scale GPU-based model training and cloud computing Knowledge of synthetic biology or regulatory sequence design Previous
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including code design, documentation and testing. Familiarity with optimization methods including Machine Learning (ML) techniques. Any experience with computations on GPUs. Working knowledge of Linux command