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of metabolic pathways essential for biosynthesis and redox balance. We investigate how p53 integrates metabolic cues by functioning as both a sensor and regulator of cellular metabolism. In parallel, we seek
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interests, you will have the opportunity to work with: High‑throughput functional genomics: pooled CRISPR and base‑editing screens, barcoded overexpression libraries, massively parallel reporter assays
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foundations of economic decision-making, using behavioral experiments and computational modeling. The program is especially interested in research that explores parallels between the cognitive mechanisms
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workloads. Conduct research on language front‑end abstractions, mixed‑precision modeling, heterogeneous parallelism, and MLIR-level transformations. HPC System Co‑Design: Work with domain scientists and
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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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adapting large-scale codes developed for parallel computing. Record of excellence in professional achievement, as evidenced by a strong publication record. Demonstrated ability to carry out independent
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computing software libraries (e.g., Trilinos, MFEM, PETSc, MOOSE). Experience with shared and distributed memory parallel programming models such as OpenMP and MPI. Experience with one more GPU or performance
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also include trouble shooting capabilities. Desirable skills include working knowledge of Linux, FORTRAN, Python and C++; experience with machine learning, parallel computing and high-performance
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, turbulence, CFD, numerical methods, and turbulent combustion. • Proficiency in HPC environments (parallel computing on CPU/GPU systems) • Demonstrated publication record in reputable journals/conferences
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environments. Experience with parallel computing environments, HPC in a Linux environment. Experience with surrogate modeling. Experience with data analytics techniques. Familiarity with C++ and GPU programming