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requires not only expertise in LLMs and machine learning but also an understanding of the unique challenges posed by scientific data, which often includes large-scale numerical datasets, complex simulations
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
modeling of large-scale dynamics in networks. This role involves creating large scale models of dynamic phenomena in electrical power networks and quantifying the risk of rare events to mitigate
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computational science expertise. ALCF is seeking a postdoctoral researcher to join our team focused on advancing data infrastructure and AI applications on supercomputing systems. This position offers an exciting
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for a predoctoral/postdoctoral researcher position in research data management. Position Overview The candidate will manage and coordinate data activities across ESRA. You will work closely with
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computational science expertise. The ALCF has an opening for a postdoctoral position in data management targeting AI applications at scale. This Postdoc will join the AL/ML group, a vibrant multidisciplinary team
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models; 2. Statistical methods, analysis, and inference for large-scale computational simulator applications; 3. Uncertainty representation, quantification and propagation; and 4. Scalable data science
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, modeling and analysis, integrating diverse data sets to identify global risks affecting sourcing strategies. In this role you will: Conduct and contribute to research and model development to enhance
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. Integrate deep mutational scanning data to assess viral fitness and immune escape, collaborating with experimental virologists. Work with large-scale genomic and proteomic datasets from BV-BRC, GISAID, and
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. This position offers an exciting opportunity to work at the intersection of HPC and AI, addressing critical communication bottlenecks and optimizing network interconnects for large-scale distributed systems
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or more of the following: Experience with large-scale molecular dynamics (MD) simulations using software such as LAMMPS. Experience in handling and data analysis generated from multi-million to multi