Sort by
Refine Your Search
-
experiment at the EIC. The program includes data analysis involving polarized targets at Jefferson Lab as well as full detector and physics simulations for ePIC. In addition, the candidate will collaborate
-
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
-
will collaborate closely with NSLS-II staff while developing cutting edge sample preparation and data analysis techniques that enable the next generation of the XCFS methodology. In addition
-
complex terrain regions. CMAS does this by innovating on the fronts of meteorological data acquisition, analysis, and interpretation (https://www.bnl.gov/cmas/). The CMAS work portfolio is conducted within
-
a related field Experience with radiation transport codes (e.g., FLUKA, Geant4, MCNP etc.) Excellent programming and data analysis skills (e.g., Python, C++, or similar) Solid understanding
-
, 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
-
computational resources for data analysis. This position offers a dynamic, collaborative environment, engaging with experts across plant biology, microbiology, structural biology, and computational sciences and
-
.) and electrical device data analysis including transistor characteristics. You communicate effectively, verbally and in writing, evidenced by peer-reviewed publications and conference presentations
-
artificial intelligence (AI) and machine learning (ML) methodologies and interested in advancing these tools for accelerating the analysis of the big data acquired by electron microscopy. • You work
-
and relevant data analysis. • Demonstrated experience in Python programming. • Knowledge of machine-learning algorithms. Additional Information: BNL policy requires that after obtaining a PhD