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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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PhD (typically completed within the last 0-5 years) in pyrometallurgy, chemistry, materials science, chemical engineering, or related scientific background with 0-3 years’ experience. Experience in
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become part of a new holotomography software package actively being developed by the team. Position Requirements Required Knowledge, Skills, and Experience: PhD (recently completed or soon-to-be completed
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have the opportunity to be a part of a world-class scientific team and lead tasks in vigorous research programs. Position Requirements A PhD in Physics, Materials Science or a related field; received
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engineering controls such as gloveboxes or hoods is desired, but not mandatory. Strong interpersonal, written, and oral communication skills. Ability to model Argonne’s Core Values: Impact, Safety, Respect