INTERNSHIP DETAILS

Research and Development Intern, PhD Track

CompanyTractian
LocationAtlanta
Work ModeOn Site
PostedOctober 1, 2026
Internship Information
Core Responsibilities
The intern will define and execute a focused research problem by implementing models and experiments to test hypotheses. They will document findings, compare approaches against baselines, and deliver a technical report with recommended next steps.
Internship Type
intern
Company Size
881
Visa Sponsorship
No
Language
English
Working Hours
40 hours
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About The Company
Tractian provides asset intelligence solutions that combine hardware sensors and AI software to monitor machine health in real time, so industrial teams can catch failures before they happen, prioritize what matters, and act with confidence. Our approach is built on physical AI: sensors deployed directly on critical assets, feeding AI models trained on data from the largest industrial database available. The result is asset intelligence that goes beyond alerts, telling you what's wrong, why, and what to do next before a failure becomes a breakdown. Trusted by 1,500+ manufacturers across the Americas - including McKesson, Air Liquide, Verizon, Cummins, Ingredion, and Whirlpool - Tractian has returned $304M to customers through earlier failure detection and helped teams avoid 97,631 hours of downtime. Tractian was named to the Forbes AI 50 and ranked #24 Fastest-Growing Company in North America on the Deloitte Technology Fast 500™. A smarter way to monitor, prioritize, and act. Learn more at tractian.com.
About the Role
Research and Development at Tractian
Research and Development turns open technical questions into tested approaches. This track combines quantitative research, programming and experimentation to explore problems relevant to Tractian’s products and business.

What You Will Do
Own a focused research problem with guidance from an engineering mentor. Define the question, implement a baseline and compare alternative approaches. Use the results to explain what works, what remains uncertain and what the team should investigate next.

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.

Requirements
  • 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. 

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

What You Will Gain
Experience applying doctoral research skills to a practical technical problem, with mentorship on experimentation, implementation and communicating findings that inform engineering decisions.
Key Skills
PythonMathematical modelingStatisticsExperimental designPredictive modelingOptimizationScientific computingTime-series analysisNumPyJAXPyTorchData analysisResearch methodologyTechnical writing
Categories
Science & ResearchTechnologyEngineeringData & AnalyticsSoftware