The Role
Conduct focused technical research under engineering mentorship. Define research questions, formulate hypotheses, implement Python models and experiments, compare approaches against baselines, evaluate generalization and computational cost, and deliver reproducible code with a concise technical report. The role applies quantitative research, mathematical modeling, statistics, optimization, predictive modeling, scientific computing, and time-series analysis to practical product and business problems.
Summary Generated by Built In
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.
Skills Required
- Currently pursuing a PhD in Physics, Computer Science, Machine Learning, Engineering, Applied Mathematics, Statistics, or a related quantitative field.
- Strong Python programming skills.
- 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 evidence-based findings.
- Experience with predictive modeling, optimization, scientific computing, or time-series analysis.
- Familiarity with NumPy, JAX, or PyTorch.
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The Company
What We Do
Tractian is a machine-intelligence company delivering integrated hardware, cloud software and AI to prevent machine failures and boost industrial uptime. Their offering combines vibration and condition sensors, TracOS maintenance-management software, and AI-driven analytics to enable predictive maintenance, energy optimization and operational visibility for factories and asset-heavy operations globally.
