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ideal for a researcher who possesses working fluency across both computational AI architectures and physical lab automation. We are seeking someone with an eagerness to master missing domains and a strong
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software, and heterogeneous execution environments. Explore and analyze different quantum computing modalities and architectures and investigate their integration with HPC systems. Use representative
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advanced epidemiological methods and appropriate statistical software. While no one specific programing language is preferred, the ability to do advanced data cleaning and statistical analyses is required
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. Department Functions Investigate the role of three-dimensional chromosomal architecture in cancer development and progression. Maintain, propagate, and bank mammalian cell lines using strict aseptic techniques
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and technologies. Knowledge of AI/ML is important, but the focus will be on the high-fidelity simulation environments, software networking bridges, and physical data collection architectures
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fundamental research in physics-informed and symmetry-aware machine learning for nonadiabatic excited-state molecular dynamics. Develop and evaluate equivariant graph neural networks and related architectures
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understanding of parallel application development techniques (parallel programming models, algorithms, and software) Preferred Qualifications: Experience in implementing ab initio simulation codes such as VASP
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Computing (HPC) system architecture and intelligent storage design. The candidate will contribute to research and development efforts in scalable storage and memory architectures, telemetry-driven system
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development, intelligent software architecture and design, automated testing and verification, code generation and repair, DevOps and deployment automation, software maintenance and evolution, software
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Confidential Computing and Secure Multi-tenancy. The candidate will be able to make research contributions in areas of system software architectures to support secure computing enclaves on large scale HPC and