Research and Development Intern, PhD Track

Summary

TRACTIAN is seeking a Research and Development Intern, PhD Track to investigate technical problems relevant to its products and business through quantitative research, programming, and experimentation. The intern will define research questions, implement and compare computational approaches, assess results, and communicate findings through reproducible code and technical reports.

Responsibilities

• Review relevant research and translate an open problem into testable hypotheses
• Implement models and experiments in Python, documenting data, assumptions and methods
• Compare approaches against meaningful baselines; assess generalization, failure cases and computational cost
• Deliver reproducible code and a concise technical report explaining the findings, limitations and recommended next steps

Skills

• Currently pursuing a PhD in Physics, Computer Science, Machine Learning, Engineering, Applied Mathematics, Statistics or a related quantitative field
• Strong Python programming skills and foundations in mathematical modeling, statistics and experimental design
• Research experience developing or evaluating computational methods through code and experiments
• Ability to investigate unfamiliar problems independently, question assumptions and communicate what the evidence supports
• Experience with predictive modeling, optimization, scientific computing or time-series analysis
• Familiarity with tools such as NumPy, JAX or PyTorch is useful
• Papers, research software and technical projects are welcome; publications are not required

Qualifications

Must Haves

• Currently pursuing a PhD in Physics, Computer Science, Machine Learning, Engineering, Applied Mathematics, Statistics or a related quantitative field
• Strong Python programming skills and foundations in mathematical modeling, statistics and experimental design
• Research experience developing or evaluating computational methods through code and experiments
• Ability to investigate unfamiliar problems independently, question assumptions and communicate what the evidence supports
• Experience with predictive modeling, optimization, scientific computing or time-series analysis

Nice to Haves

• Familiarity with tools such as NumPy, JAX or PyTorch is useful
• Papers, research software and technical projects are welcome; publications are not required

Benefits

• Remote work arrangement
• Mentorship on experimentation, implementation and communicating findings that inform engineering decisions
• Experience applying doctoral research skills to a practical technical problem