SandboxAQ

Postdoctoral Researcher – Machine Learning for Materials and Alloys

SandboxAQ

full-time

Posted on:

Origin:  • 🇺🇸 United States

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Salary

💰 $115,000 - $125,000 per year

Job Level

Mid-LevelSenior

Tech Stack

Cyber SecurityPythonPyTorchScikit-LearnTensorflow

About the role

  • Develop and apply ML and optimization techniques to guide lightweighting strategies.
  • Use reasoning-based ML approaches to evaluate trade-offs among performance, manufacturability and other criteria.
  • Apply Bayesian optimization and related uncertainty-aware methods to balance performance, manufacturability, and other constraints.
  • Build reproducible workflows that integrate materials data, manufacturing methods, and simulation outputs.
  • Curate and analyze structured datasets on materials, processing routes, and mechanical properties to support ML pipelines.
  • Collaborate with engineers and computer scientists to connect ML outputs with structural and materials design tasks.
  • Write technical reports and present results to technical and non-technical stakeholders.

Requirements

  • U.S. citizenship is required due to USG contract requirements.
  • PhD in Materials Science, Metallurgy, Mechanical Engineering, Computational Materials Science, Applied Physics , or a related field.
  • Demonstrated experience applying ML or statistical methods to materials or engineering applications.
  • Proficiency in Python and ML frameworks (PyTorch, TensorFLow, Scikit-learn).
  • Familiarity with optimization and uncertainty quantification methods such as Bayesian optimization, Gaussian processes, ensemble learning, or related approaches.
  • Strong research track record, evidenced by publications in materials science, ML, or computational design.
  • Excellent problem-solving and communication skills.