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that incorporate latest machine-learning algorithms). Furthermore, the successful candidate will collaborate broadly with the other members of IO and CFN, leveraging their expertise in design and fabrication
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analysis of atmospheric numerical model output (e.g., WRF, PALM, SAM) Experience with machine learning and artificial intelligence techniques Experience with predictive modeling Environmental, Health
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operation of particle or nuclear physics detectors Experience in applying machine learning to scientific problems Experience in distributed computing, workflow management and/or data management software
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and the ability to learn new things and be able to multi-task, be deadline driven, detail oriented, ability to work on a team, and someone who wants to grow within the organization. It is a great
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, and Abilities: Experience in NGS library preparation and data analyses. Bioinformatic/programming skills (MatLab, Python, R, etc). Experience in application of Artificial Intelligence/Machine Learning
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, enhanced by machine-learning and data-driven analysis techniques. Additionally, the study will encompass electrically triggered events that mimic the voltage-based signaling of biological synapses
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control under high inverter-based resources (IBRs). • Develop and apply artificial intelligence (AI)/machine learning (ML) techniques for power system planning, operation, control, and cybersecurity
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, adhering to a Design-Build-Test-Learn methodology for integrated research. Within the Schwender group, the primary objective is to assess the outcomes of metabolic engineering endeavors aimed at enhancing
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applications to accelerator systems Use of Machine Learning tools Excellent written and verbal communication skills. Proficiency with standard MS Office tools including Excel, PowerPoint and Word. Preferred
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out R&D programs focused on Electro-Photonics, Quantum Information Science, Artificial Intelligence & Machine Learning, and Neuromorphic Processing that require ASICs with specific layouts