Role description
TRACTIANResearch 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.