Sort by
Refine Your Search
-
development and is the nexus of a broad collaboration network. Each year, CFN staff members support the research of nearly 600 external facility users. Three strategic nanoscience themes underlie the CFN
-
, and support proposal development. Required Knowledge, Skills, and Abilities: Ph.D. in Physics, Computer Science, Applied Mathematics, Engineering, or a related field. Strong programming experience
-
scientists to plan and execute interdisciplinary experimental campaigns. Maintain and contribute to analysis software and simulation tools for experimental planning and data reduction. Required Knowledge
-
the development of new radical scavengers for the conversion of radiolytic solvent radicals into secondary reductants/oxidants or unreactive species. Exploiting the knowledge gained from the above mentioned studies
-
the operation, software, and computing of the ATLAS experiment. Required Knowledge, Skills, and Abilities: Ph.D. in experimental particle or nuclear physics or related field. Experience with data analysis and
-
essential for progress on all aspects of this program. Required Knowledge, Skills, and Abilities: Ph.D. in experimental particle or nuclear physics or related field. Experience with high- and medium-energy
-
papers and presenting work at seminars and conferences. Required Knowledge, Skills, and Abilities: PhD in physical chemistry, or a related field. Preferred Knowledge, Skills, and Abilities: Experience in
-
Knowledge, Skills, and Abilities: Candidates should have a Ph.D. in theoretical physics with demonstrated expertise in the area of high energy physics. Candidates should have demonstrated abilities in
-
—an essential characteristic for replicating neural network behavior. The position offers a unique opportunity to engage in cutting-edge research at the intersection of quantum materials and advanced electron
-
proposals for ongoing research program Required Knowledge, Skills, and Abilities: Ph.D. in physics or related discipline within the last 5 years Strong background in condensed matter physics Data analysis