Sort by
Refine Your Search
-
engineering teams to evaluate energy deposition, power losses, total ionizing dose, and other radiation-relevant quantities across the Electron Storage Ring (ESR), Hadron Storage Ring (HSR), and Rapid Cycling
-
Light Source II (NSLS-II). NSLS-II is a user facility dedicated to helping researchers from the U.S. and abroad bring cutting-edge synchrotron technology and automation to bear on society’s most pressing
-
materials for the next generation of microelectronics and quantum information science and technology. Position Description: We are looking for a Postdoctoral Research Associatefor a 1-year term , to grow high
-
research findings via paper publications and external presentations. Required Knowledge, Skills, and Abilities: You have a Ph.D. in a relevant discipline (Materials Science, Physics, Electrical Engineering
-
. POSITION REQUIREMENTS: Required Knowledge, Skills, and Abilities: Ph.D. in Electrical Engineering, Computer Engineering, Computer Science, Physics, Material Science, or related discipline. Demonstrated
-
have earned a Ph.D. in a relevant discipline (Materials Science, Physics, Chemistry, or a related engineering discipline) within the past five years or will complete your degree before the starting date
-
Requirements: Required Knowledge, Skills, and Abilities: Ph.D. in computer science or a related field (e.g., engineering, applied mathematics, statistics, physics) awarded within the last 5 years. Strong
-
the department on new potential collaborations. Position Requirements: Required Knowledge, Skills, and Abilities: Ph.D. in computer science or a related field (e.g., engineering, applied mathematics, statistics
-
achievements, and engage within and beyond the group on new potential collaborations. Required Knowledge, Skills, and Abilities: Ph.D. in computer science or a related field (e.g., engineering, applied
-
. in computer science or a related field (e.g., engineering, applied mathematics, statistics) awarded within the last 5 years. Strong theoretical understanding and practical experience in deep learning