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-optimization of industrial end-use systems and energy supply systems. Build reproducible computational workflows for data processing, model development, calibration, validation, and scenario analysis. Develop
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. The project will involve development of novel parallel algorithms to facilitate in-situ analyses at-scale for multi-million and multi-billion atom simulations. In this role, you can expect to work on enhancing
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
mathematics, or a related field Candidates should have expertise in two or more of the following areas: Uncertainty quantification, numerical solutions of differential equations, and stochastic processes
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). Expertise in data and model parallelisms for distributed training on large GPU-based machines is essential. Candidates with experience using diffusion-based or other generative AI methods as
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range of molecular systems, including: Transition-metal complexes (e.g., chiral ruthenium and iridium complexes) Local and nonlocal inner-shell decay processes in solvated ions and transition-metal
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conducted by developing intelligent systems that can function as collaborative partners in the scientific process. Our group is pioneering the development of (1) generative AI models and agentic architectures
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develop computational fluid dynamic (CFD) tools that make exascale computing accessible to a broader set of users. The successful candidate will develop a massively parallel solver, capable of running
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(HPC): Experience with parallel computing (MPI, OpenMP, CUDA/HIP) or running workflows on supercomputing clusters. Software Engineering: Knowledge of version control (Git), containerization (Docker
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fluorometric profiles of cyanobacteria using devices such as the Beckman Coulter Cytoflex Bioinformatics – Basic scripting experience in languages such as Python, R or BASH to carry out rudimentary genomics
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processing of information and work associated with day-to-day operations as assigned. Responsibilities include, but are not limited to : Researching, compiling, and tracking, and analyzing data and information