35 electrical-machine-"https:"-"https:"-"https:"-"https:"-"https:" Postdoctoral positions at Argonne
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characterization, and machine learning. The role offers the opportunity to leverage Argonne’s world-class scientific capabilities and engage with a strong network of internal and industry collaborators. Position
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current sensors) Develop and characterize superconducting nanowire single-photon detectors (SNSPDs) using high kinetic inductance materials such as NbN, TiN, and NbTiN, targeting high detection efficiency
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operando experiments under electrical, thermal, or mechanical bias to capture real-time defect dynamics. Integrate multimodal datasets and collaborate with AI/ML teams for data fusion, physics-informed model
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Manufacturing group perform science-based membrane synthesis and scaleup development by using roll-to-roll manufacturing and machine learning enabled in-line characterization and quality control methods
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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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-the-loop exploration of extreme-scale scientific data. This position sits at the intersection of scientific visualization, agentic AI systems, human–computer interaction (HCI), and high-performance computing
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fabrication facilities Access to the Center for Nanoscale Materials (CNM) Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in physics, electrical engineering, materials
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it in Physics with a focus on accelerator physics, or Electrical Engineering with a focus on RF/Accelerator Physics Strong background in accelerator physics and beam diagnostics. Excellent problem
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field Experience leveraging artificial intelligence or machine learning in the development of battery electrolytes and catalyst materials Demonstrated expertise in lithium–sulfur battery materials and
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domains such as nontrivial skyrmions, using external stimuli (e.g., optical excitations, electric and magnetic fields) and internal nanoscale heterogeneity, defects, and interfaces (e.g., twisting