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activities. This is an exciting opportunity to work within a collaborative group with deep expertise in silicon detectors, Trigger/DAQ (TDAQ) systems, software, and computing. The Argonne ATLAS group plays a
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for next-generation information processing, microelectronics, wireless communication, and quantum information science. Key Responsibilities: Develop terahertz coplanar resonators, including design
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together computer scientists, AI researchers, domain scientists, software engineers, and high-performance computing experts. You will help design and implement new methods for multimodal federated learning
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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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-friendly software interfaces that enhance data accessibility of data and insight for diverse stakeholders. Facilitate ongoing communications and foster relationships with a broad array of stakeholders
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. The successful candidate will work in the Data Science and Learning division of the Computing, Environment, and Life Sciences directorate of Argonne National Laboratories. Primary responsibilities will be
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computational scientists, economists, engineers, and other researchers to develop data-driven, decision-relevant analytical tools for complex industrial systems. Key Responsibilities: Develop, improve, and apply
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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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sensing, quantum information science, superconducting circuit, or magnonics. Proficiency in scientific software development (e.g., Python, COMSOL, HFSS or similar languages). Ability to model Argonne’s core