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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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spintronics, or cavity spintronics. Proficiency in scientific software development (e.g., Python, COMSOL, HFSS). Demonstrated ability to work independently and collaboratively in a multidisciplinary environment
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of both hardware and software tools for operando characterization under electrochemical conditions, as well as the management and analysis of large experimental datasets. The successful candidate will
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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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, presentations, software, datasets, and internal reports Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in chemistry, chemical engineering, materials science, polymer science
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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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measuring MEMS devices, as well as designing feedback loops and control algorithms for their precise operation Experience using software tools to simulate the physical properties and behavior of MEMS
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deep learning including data collection, architecture development, model training, and validation Interest in software development, with particular emphasis on the Python programming language and
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, we encourage applicants to consider how their data processing and software development capability fits into the proposed work and future direction. The Postdocs will be working directly with assigned
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, we encourage applicants to consider how their data processing and software development capability fits into the proposed work and future direction. The Postdocs will be working directly with assigned