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collaborative, multidisciplinary environment that brings together expertise in quantum information science, computer systems, networking, high-performance computing, and scientific applications. The scientist
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operating experimental systems for separation processes; conducting laboratory-scale studies involving radiotracers and actinide/lanthanide separations; supporting the development and optimization of aqueous
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The Chemical and Fuel Cycle Technologies Division is seeking a Postdoctoral Appointee to conduct research in chemical process engineering, separations, and process intensification for recovery
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, focused ion beam specimen preparation, and computer vision or machine-learning analysis of microscopy datasets. The position requires strong experimental, analytical, written, oral, and interpersonal
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language. Working knowledge of UNIX or Linux. Preferred Knowledge, Skills, and Experience Experience with machine learning and accelerator operation. Experience working with complex algorithms. Experience
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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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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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the development of novel research concepts. The scientist will lead Argonne’s Rapid Prototyping Laboratory (RPL), a team of computer scientists, roboticists, data scientists, and subject matter experts
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expertise in machine learning, computational imaging, computer vision, or signal processing. Proficiency in scientific programming and modern ML frameworks, with the ability to implement and debug research
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applying artificial intelligence (AI) and machine learning (ML) methods for the autonomous, self-driving synthesis of nanoscale and quantum materials. This is an exciting opportunity to help shape a new