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https://bayt.page.link/v1TUmrkCw1dqRip19
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Remote
10 Open Positions
Contractor
500 Employees or more · Scientific Research & Development

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Job description

Job Title: Computational Physics Expert


Job Type: Contractor


Location: Remote


Job Summary: In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input.


Key Responsibilities:

  1. Leverage deep expertise in computational physics to contribute high-quality insights to AI evaluation projects.
  2. Analyze, interpret, and synthesize large-scale scientific data sets and experimental results.
  3. Develop, review, and refine quantitative models, simulations, or workflows in relevant physics domains.
  4. Collaborate with interdisciplinary teams to inform and improve AI model capabilities in scientific reasoning.
  5. Apply advanced numerical methods and computational techniques to real-world physics challenges.
  6. Document findings and communicate complex concepts clearly in both written and verbal formats.
  7. Maintain high standards of scientific integrity and accuracy in all project deliverables.


Required Skills and Qualifications:

  1. PhD in physics or a closely related field, or equivalent industry/research experience.
  2. Expertise in computational physics, scientific computing, or simulation-heavy research is desirable.
  3. Proficiency with Python, C++, MATLAB, and scientific tools such as ROOT would be ideal.
  4. Experience working with numerical simulations, Monte Carlo methods, or HPC workflows.
  5. Strong analytical, quantitative, and mathematical reasoning abilities.
  6. Demonstrated experience in experimental or scientific data analysis.
  7. Excellent written and verbal communication skills; ability to convey complex topics to diverse audiences.


Preferred Qualifications:

  1. Background in particle physics, astrophysics, plasma/fusion, or quantum systems.
  2. Experience with AI/ML workflows, scientific benchmarking, or evaluation practices.
  3. Track record of published research or contributions to scientific literature.
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