Quantum Dot Process & Characterisation Engineer- Post-Growth Processing (Master)

Quandela stands as a global leader in quantum computing, driven by groundbreaking technology and a strategic vision for scaling quantum solutions. The company’s unique ability to offer both hardware and software solutions, along with its commitment to build energy efficient datacenters and scalability, positions it to play a key role in the next wave of innovation, and in many strategic and sovereign industrial sectors. Join Us at the Forefront of Quantum Computing Innovation 🚀 Role overview We are looking for a Process & Characterisation Engineer to prepare and validate GaAs/AlGaAs samples containing InAs quantum dots (QDs) through the first steps of our single-photon source fabrication flow. The role combines hands-on cleanroom processing – chemical treatment, PECVD deposition and high-temperature annealing – with optical characterisation of the QDs before and after each step. The data you produce decides whether a sample is ready to move forward, and how the process recipes should be adjusted. You will start by running an established, well-documented procedure with rigour and consistency. As you build expertise, the role is designed to grow: within your first year, you will contribute to optimising the process, automating the measurement setups and taking ownership of sample validation for these steps, working closely with both the Production and R&D teams. Sample preparation & processing (from day one) Run the established step-by-step procedure for preparing GaAs/AlGaAs samples with InAs quantum dots. Carry out the cleanroom fabrication steps: chemical surface treatment, PECVD deposition and high-temperature annealing. Follow recipes and operating procedures precisely, and flag any deviation, drift or anomaly as soon as it appears. Contribute to a safe, disciplined and efficient cleanroom environment. Optical characterisation & validation Measure QD optical properties before and after processing, using photoluminescence and white-field imaging, including at cryogenic temperature. Compare pre- and post-processing results against acceptance criteria to decide whether each sample can be released to the next fabrication steps. Adjust process recipes based on measurement results, within defined process windows. Data, reporting & traceability Analyse measurement data using Python and report results clearly and regularly to the Production and R&D teams. Maintain the sample database so that every sample’s processing history and measurements are fully...

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