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conferences (e.g., NeurIPS, SC, AAAI, or domain-specific venues like Fusion Science or Computational Materials). Collaborative mindset in team environments and across disciplines. Special Requirements: Postdocs
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computational experts to conduct efficient analyses leading to discovery in mammalian neuron genome structure-function data. In parallel, trains to achieve mastery and excellence in running code written by other
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computational experts to conduct efficient analyses leading to discovery in mammalian neuron genome structure-function data. In parallel, trains to achieve mastery and excellence in running code written by other
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software for multi-arch environments Development in high-performance computing (HPC) or distributed systems Strong understanding of Linux toolchains, build systems (CMake), and debugging tools Parallel
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Postdoctoral Fellow - Materials Chemistry, Texas Materials Institute, Cockrell School of Engineering
or parallel reactors Collaborate with computational scientists to integrate machine-learning models for closed-loop materials discovery Collaborate with companion postdocs on functional materials
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toolchains, build systems (CMake), and debugging tools Parallel computing libraries (MPI, RPC, Mercury, Margo) Experience with HTML and web technologies. Cloud computing platforms and web deployment