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within a multi-disciplinary research environment consisting of computational scientists, computer scientists, electrical engineers, domain scientists, and applied mathematicians conducting basic and
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challenges. Our research and development capabilities include radar and optics technologies, radio frequency (RF) communications, computational imaging, artificial intelligence / machine learning (AI/ML
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. Basic Qualifications: PhD in electrical/computer engineering, computer science, or a related discipline A minimum of 8 years of relevant experience in image/signal processing and machine learning
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-body ab-initio methods for description of electronic, magnetic, and vibrational properties in a range of materials Expertise with artificial intelligence and machine learning approaches will be also
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to DOE sponsors, industrial partners, and international collaborators. Basic Qualifications: PhD in Computer Science, Computer Engineering, or a field closely related to the job duties of this position. A
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. Basic Qualifications: A PhD in Materials Science & Engineering, Physics, Chemistry, or a related field completed within the last 5 years A minimum of 2 years of post-Ph.D. experience utilizing
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in urban-scale building energy modeling, software development (esp. Python), or Artificial Intelligence/Machine Learning (AI/ML) Strong ideation, writing, and communication skills for establishing
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or PhD in Computer Science, Computer Engineering, Cybersecurity, or related fields with 2-4 years of experience. Proven experience architecting and implementing complex distributed systems tailored
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Qualifications: Advanced degree (MS or PhD) in Computer Science, Data Science, Geospatial Science (GIS/remote sensing), Electrical/Computer Engineering, or a closely related discipline. Minimum of 10–12 years