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Field
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simulations (such as GEANT4 or MCNP); experience conducting original scientific research as well as publishing in scientific journals; and the ability to communicate effectively and work in a dynamic, fast
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-resolution dosimeter, and new algorithms. Following this, the candidate will parameterize a Monte Carlo-based dose calculation system (e.g., GATE, TOPAS, or Geant4-based simulation tools) for evaluation in
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nuclear or particle physics research. Proficiency in scientific computing, including experience with simulation frameworks such as Geant4, ROOT, or similar toolkits. Experience with detector hardware, data
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Stanford University / SLAC National Accelerator Laboratory | Menlo Park, California | United States | 1 day ago
or superconducting sensors a plus) Vacuum / noble liquid systems Dilution refrigerators and superconducting detectors Detector simulation using Geant4 and/or G4CMP Statistical data analysis Collaborative experimental
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, GEANT4) will be an advantage. A background in radiation oncology or medical physics will be an advantage. Excellent written and verbal communication skills. Experience with cloud computing and big data
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researchers. Required Skills Nuclear Instrumentation and Advanced Detection Techniques: Proficiency in detecting ionizing radiation and using Monte Carlo simulation software (MCNP, GEANT4). Knowledge of multi
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this will include: Demonstrated expertise in data analysis and simulation Familiarity with C++; and proficiency in the use of ROOT and Geant4, and interest in machine learning techniques Knowledge
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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
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applications. Radiation detector response measurement and characterization experience. Familiarity with radiation transport simulation codes such as GEANT4 and PHITS. Familiarity with AI-tools used for image