Day-to-Day Responsibilities
Reading recent research in quantum computing, quantum algorithms and machine learning to decide which ideas are worth testing.
Designing hybrid algorithms that use a quantum processor for part of a learning task, such as feature mapping or optimisation, and a classical computer for the rest.
Writing code in Python and quantum software frameworks to simulate quantum circuits and test models on small datasets.
Running experiments on quantum simulators and, where access is available, on real quantum hardware, and recording the effects of noise and errors.
Comparing quantum models against classical machine learning baselines to check whether a quantum approach gives any real benefit.
Writing research papers, technical reports and patent drafts, and presenting results to colleagues and clients.
Working with hardware engineers, physicists and software teams to turn promising prototypes into tools others can use.
