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include the porting of lattice QCD libraries to the Exascale Architectures (e.g. Frontier at OLCF) and/or emerging programming models (HIP, SYCL, Kokkos, etc), software optimization and/or algorithmic
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parallel, the rare-earth solid-state system will be coupled to microwave resonators to explore future connections to superconducting qubits. The project will conclude with a demonstration of quantum gate
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Language Models (LLMs). Distributed Machine Learning: Specialization in data parallelism, model-parallelism, and collective communication strategies in large-scale environments. Proficiency in frameworks
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research project in any of several areas relevant to this topic, and to explore multiple lines of research in parallel. Most projects employ a combination of bacterial genetics, high throughput genetic
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to this topic, and to explore multiple lines of research in parallel. Most projects employ a combination of bacterial genetics, high throughput genetic screens, biochemistry, ribosome profiling (ribo-seq
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clinical care. The position is intended to provide intensive methodological training, opportunities for scientific leadership, and support for developing an independent research program. The project centers
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in C++/Java/Fortran 90, Python/MATLAB, and MPI-based parallel computing Strong publication record as first author in peer-reviewed journals Preferred qualifications Experience with 3D conjugate heat
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, rheology, parallel computing and strong analytical skills. PREFERRED: Familiarity with electrolytes; or experience with AI-based chemical discovery. Research scientist position will be offered
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Familiarity with brain imaging analysis acquisition Knowledge of multivariate statistics and/or digital signal processing Proficiency in Python. Parallel computing processing experience is highly appreciated
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. Demonstrated programming ability and knowledge of Python and/or C++. Experience with deep learning frameworks like PyTorch and application on high-performance computing (HPC) environments using distributed data