11 algorithm-development-"Multiple"-"Prof"-"Prof"-"Simons-Foundation"-"U.S" Postdoctoral positions at Brookhaven Lab in United States
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interaction physics, precision calculations of (g-2) and PDF determinations, and the development of new algorithms, among others. Position Description The successful candidate will be expected to conduct
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with a highly competitive salary. Essential Duties and Responsibilities: Conduct research and develop novel AI/ML algorithms and solutions. Disseminate research findings in publications, posters, project
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by publication record). Excellent programming and computer science skills. Preferred Knowledge, Skills, and Abilities: Practical experience developing novel ML and NLP algorithms and models and
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learning field. Excellent programming and computer science skills. Preferred Knowledge, Skills, And Abilities Practical experience developing novel ML, LLM, or CV algorithms and models. Experience with state
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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
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scattering. This work is to be done as a part of a BNL Laboratory Directed Research and Development (LDRD-B) project, focused on gathering experimental characterization of materials predicted to have non
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and national challenges. Position Description The Electron-Ion Collider (EIC) Directorate has an opening for a Postdoctoral Research Associate to support the development and implementation of radiation
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their utilization. The CMPMSD at Brookhaven National Laboratory seeks applicants for a research associate position participating in the development, understanding, and characterization of novel quantum
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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
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., crowd sourced data or from mobile and distributed instrument networks) Assess the performance of next-generation predictive urban climate models using observations Develop new visualization strategies