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bench scale micro-computed tomography and ultrasonic sensing methods to evaluate the state of charge and state of health of iron- and lead-based electrodes. Your research will be complemented by studies
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ideal for someone who enjoys working at the intersection of data science, machine learning, materials research, and experiment, and who is motivated to translate computational advances into real
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developing computational models based on mass, momentum, and energy balance principles Strong skills in applying AI tools and agentic workflows to scientific research Some experience in proposing, planning
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Position Overview We are seeking a Postdoctoral Appointee to join the Computational Science and Artificial Intelligence Group in the X-ray Science Division of the Advanced Photon Source (APS
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, composite processing, and manufacturing science to establish structure-processing-property relationships that enable high-performance multifunctional materials. The candidate will work closely with scientists
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Required Skills and Qualifications: Ph.D. completed within the last 0–5 years in computer science, data science, biomedical informatics, computational biology, bioengineering, applied mathematics, electrical
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development to support program growth Maintain laboratory instruments, equipment, and facilities in support of research operations Build and maintain active engagement with external academic and scientific
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-completed Ph.D. within the last 0-5 years in Atmospheric Science, Meteorology, Climate Science, Applied Mathematics, Data Science, or a related field with strong quantitative and computational research
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platform for X-ray absorption spectroscopy by integrating LLMs, scientific machine learning, physics-aware workflows, and strong computational chemistry/electronic-structure expertise. The researcher will
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physics, engineering, or a closely related field Experience in experimental physics/engineering, nanofabrication, quantum information science, and/or microwave and superconducting device characterization