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Field
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skills Excellent scientific writing ability and good communication skills Knowledge of scientific programming language(s), computer simulation, and quantum computing algorithms All tasks and job
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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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Qualifications - Experience in developing algorithms for analysis of biological data. - Experience with single cell and spatial transcriptome data analysis. - Experience in supervised and unsupervised machine
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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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of machine learning algorithms and experience in machine learning applications related to thermal fluid problems and/or nuclear reactor analysis. Job Family Postdoctoral Job Profile Postdoctoral Appointee
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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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to uncover vulnerabilities in complex systems, bridging gaps between traditional testing techniques and emerging security threats. This work involves developing novel techniques, algorithms, and software
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into tangible products. Critically, this work will generate a large open-source dataset of child-created games that can inform future designs of educational games and AI algorithms. The postdoctoral fellow will