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publications, conferences, and internal reports Provide mentorship and guidance to graduate and undergraduate researchers involved in related projects Position Requirements Recent or soon-to-be-completed PhD
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are seeking an postdoctoral appointee to contribute to this research to understand the underlying physics of spin and charge based memory materials using advanced in-situ transmission electron microscopy (TEM
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Energy Systems and Infrastructure Analysis Division. We are seeking applicants with a strong technical background and expertise in international trade modeling, particularly in the upstream automotive
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, and optimize for energy efficiency HPC applications and high performance data stream analytics workloads. Use of novel accelerator designs, and automatic methods to model/predict how performance would
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, and spatial transcriptomics. Key responsibilities include: Developing AI/ML methods for image alignment across modalities Automated feature detection Predictive modeling of vascularization patterns
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, and safe laboratory practices. Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in the field of Chemistry or a closely related discipline Demonstrated expertise in
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your PhD in computer science or engineering, the physical sciences, or a related field within the last five years. Comprehensive programming proficiency, preferably in Python. Experience with machine
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models, including training, fine-tuning and inferencing, at scale. It will help us better understand and improve DAOS to meet the needs of AI-driven science applications. We expect the postdoc to help
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techniques including terahertz, optical, and x-ray radiation. Candidates with a strong background in quantum materials, ultrafast lasers, and synchrotron or FEL-based x-ray diffraction techniques are highly
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are highly preferred. Position Requirements PhD in physics or related field; received within the last 5 years or upcoming year Ability to model Argonne’s core values of impact, safety, respect, integrity, and