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Field
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system) and disordered materials is also desirable. The project will involve developing autonomous materials discovery workflows on HPC platforms that can learn structure-chemistry-property relationship in
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, and familiarity with computing in the cloud/on HPC Strong data visualization and communication skills for technical and non-technical audiences Experience with interdisciplinary or collaborative
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professionals to accelerate scientific discovery and engineering advances across a broad range of disciplines. As an important part of the broader High-Performance Computing (HPC) infrastructure, the division
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, and familiarity with computing in the cloud/on HPC Strong data visualization and communication skills for technical and non-technical audiences Experience with interdisciplinary or collaborative
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. The successful candidate will have access to dedicated high performance computing (HPC) system, multiple Krios TEMs, advanced cryo-FIB-SEM systems including Hydra-bio, Arctics, and Aquilos II with integrated
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. Demonstrated track record of publications in the field. Preferred Knowledge, Skills, and Abilities Experience with structural biology, 3D ML and biology specific AI models. Experience with HPC and surrogate
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of high-quality scientific publications, experience working with real-world health data is a plus Proficiency in Python and experience working in Linux-based HPC environments or cloud computing platforms
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Proficiency in Python and experience working in Linux-based HPC environments or cloud computing platforms Proven experience with deep learning frameworks such as PyTorch, and familiarity with multimodal data
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modeling and networked biological systems. You will work at the intersection of high-performance computing (HPC), computational biophysics, and machine learning, leveraging leadership-class computing
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AI, …) and relevant programming frameworks Advanced programming skills in relevant programming languages and contexts (e.g., Python, HPC/GPU programming, big data applications) Strong team spirit and