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Field
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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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detection efforts. In parallel, any ocean word biological productivity will almost certainly fall orders of magnitude below that on Earth, leading to lower concentrations of target compounds and/or longer
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neurons using multi-omics, cis-regulatory variants will be mapped onto these enhancers and then their function determined by Massively Parallel Reporter Assays (MPRA). The research will involve stem cell
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collaborating experimental research groups. Previous experience in computational modeling of atmospheric aerosols and parallel computing/software development is strongly desired. The term of appointment is based
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in AI to study natural and artificial minds in parallel, creating the opportunity to make discoveries about ourselves and to find new ways to understand and improve AI systems. Appointments will be
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large-scale power system simulation and model reduction techniques. • Hands-on experience with EMT/Phasor-domain-based power system transient simulator development. • Knowledge of parallel and
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, with experience in additional languages such as Fortran considered a plus. Strong knowledge of at least one parallel programming model commonly used in HPC, such as MPI, OpenMP/OpenACC, CUDA, HIP, Kokkos
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productivity while reducing external inputs. In parallel, the lab is expanding efforts to understand microbiome-associated phenotypes that contribute to drought tolerance and soil water retention. This includes
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parallel experiments involving large fly populations (e.g., lifespan and longitudinal exercise studies). Track genotypes, experimental timelines, and datasets with high accuracy. Perform molecular and
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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