86 web-programmer-developer-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" research jobs at Argonne
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research to develop sustainable innovative technologies to improve the efficiency of resource and energy utilization; to increase our economic competitiveness; and to enhance our national security
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-ion battery materials. The focus is to develop atomic layer processing methods to tailor the surface properties of lithium ion battery electrodes using nanoscale thin films and surface treatments
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through the design and synthesis of nanoscale epitaxial oxide thin films. This position supports a three-year Laboratory Directed Research and Development (LDRD) project focused on developing scalable
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The Microscopy group in X-ray Science Division of Advanced Photon Source at Argonne National Laboratory is seeking postdoctoral researchers to work on cutting-edge ptychography technique development
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readout and controls (e.g., SQUID-based time- or microwave-multiplexed systems) with beamline data acquisition and control (EPICS/Bluesky). Develop and maintain data acquisition, calibration, and analysis
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material property database for composites. The candidate will utilize the database to develop AI models for composite discovery. The candidate will work with a multidisciplinary team to set up finite element
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programming, interfacing hardware, and developing machine-learning methods highly desirable. The researcher will join an Argonne funded project with interdisciplinary team of material scientists, computer
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The Time-Resolved Research Group in the X-ray Science Division at Argonne National Laboratory invites applications for a Postdoctoral Appointee. The role focuses on developing ultrafast pump–probe
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The Dynamics and Structure Group (DYS) at the Advanced Photon Source (APS) seeks a highly motivated Postdoctoral Appointee to develop High-Pressure, High-Temperature X-ray Photon Correlation
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studies (e.g., EELS, EDS) to probe defect structures and dynamics Apply advanced image processing and analysis; develop AI/ML workflows for quantitative defect characterization Implement high-throughput and