20 algorithm-"Multiple"-"U"-"Prof" "NTNU Norwegian University of Science and Technology" Postdoctoral positions at Argonne
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PhD level with zero to five years of employment experience. Expertise in testing, characterizing, and measuring MEMS devices and designing feedback loops and control algorithms for the precise operation
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within the last 0-5 years) in computational science, mathematics, physics, or a related field with a focus on image processing. Proven experience in algorithm and software development. Expertise in Python
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encompass: Catalysts Synthesis: Utilize your expertise in materials synthesis to develop novel catalysts guided by machine learning algorithms Catalyst Performance Evaluation: Utilize aqueous electrochemical
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inverter-based resources for performing real-time simulations in Opal-RT. Develop and prototype advanced control algorithms for grid forming and grid following inverters. Develop and demonstrate
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algorithms to develop cybersecurity, optimization, and control solutions for real-world grid applications. Candidates will be required to work in at least 4 of the following areas: Build, simulate, and
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to electrochemical issues from multiple areas of materials research including TM-oxides, TM-phosphates, composite materials. Skilled in oral and writing communication skills with a good record of publication and
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for developing new computational tools and AI/ML approaches to analyze and correlate data from multiple imaging modalities, including synchrotron tomography, x-ray fluorescence microscopy, visible light microscopy
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open access of datasets. Key Responsibilities Develop and implement data management strategies to support research activities across multiple institutions. Collaborate with researchers to establish data
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that can process and learn from multiple data streams in real-time is key to unlocking the full potential of such instruments. The postdoctoral appointee will be responsible for developing such methods
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analysis of (1) decarbonization pathways for energy- and emissions-intensive industries and (2) material circularity pathways in a low-carbon future. The candidate would conduct research across multiple DOE