Rose User

I’m a research scientist focused on quantum-enhanced machine learning methods in the healthcare domain, turning complex scientific data into data-driven analysis and performance acceleration. I thrive at the intersection of data science, health science, and applied mathematics, bringing structure to technical investigations.

In my career, I contributed to research projects using hybrid quantum machine learning models built with Python and Qiskit—covering transpilation, circuit-level optimisation, and numerical simulations. I worked across interdisciplinary teams, pairing technical systems thinking with research rigor to support analytics and applied problem-solving.

I also supported open-source work in the Qiskit ecosystem on GitHub and contributed to building momentum in the community through technical workshops and learning materials. In practice, I value clear communication of methods, reproducibility, and documentation that helps others run, test, and extend research.

My approach is practical and research-driven: combine strong programming foundations (Python, SQL, Fortran, R) with machine learning workflows to evaluate models and deliver measurable insights.