Material Scientist (Hiring Immediately)

At OQC, we’re building the quantum computers that will power the next generation of scientific discovery and commercial innovation. Our mission is to put quantum in the hands of humanity and we’re looking for exceptional scientists and engineers to help us do it.

We are seeking a Materials Scientist, with a strong focus on thin film characterisation, to join our Materials Science & Device Engineering (MSDE) team. This is a hands-on, high-impact role focused on advancing our understanding of materials, interfaces and nanofabrication processes that underpin high-coherence superconducting quantum devices. You will apply advanced characterisation and data analysis techniques to guide improvements in fabrication precision, material performance and device reliability.

The Role

The Materials Scientist plays a critical role in advancing the materials and processes that underpin OQC’s quantum devices. Partnering closely with senior engineers, you will design and lead in-depth characterisation studies, extract insight from complex datasets, and turn experimental results into clear, evidence-based recommendations that directly improve qubit coherence, fabrication precision and device performance.

Working focused on materials R&D, you will combine hands-on experimental expertise with strategic technical judgement, collaborating internally and engaging external characterisation facilities when advanced capabilities are required. You will be highly skilled in thin film characterisation with strong focus on X-ray thin film characterisation techniques, these skills are key to this role.

• Investigate: Apply advanced thin film characterisation techniques with a focus on extracting quantitative information on thickness, density, roughness, crystallinity, strain and nanostructure to analyse superconducting device films and interfaces.
• Extract: Use fitting routines and specialised modeling software such as reflectivity fitting and scattering pattern analysis to extract quantitative data from thin film X-ray patterns.
• Develop and refine custom scan protocols (e.g., grazing-incidence, rocking curves, pole figures) to suit complex multilayer stacks.
• Improve : Interpret complex data sets from thin films and multilayer structures to recommend improvements of nanofabrication processes and enhance qubit coherence.
• Document: C reate and maintain clear process documentation, experimental plans and progress reports for senior stakeholders.
• Collaborate: Partner with nanofabrication engineers and other material scientists to provide subject-matter expertise and data-backed guidance on device performance.

What We’re Looking For

We value strong scientific fundamentals, intellectual curiosity, and a rigorous, evidence-driven approach to problem solving.

• Strong hands-on experience with advanced thin-film X-ray characterization techniques such as XRR, and different modes of XRD.
• Expertise in HRXRD and reciprocal space mapping (RSM) for strain and texture analysis
• Experience with grazing-incidence methods (GIXRD, GISAXS or GIWAXS).
• Proficiency in modelling and fitting X-ray data (e.g. Bruker LEPTOS, GenX, GSAS-II, TOPAS, or similar tools).
• Solid understanding of X-ray and e-beam scattering and diffraction theory.
• Experience in diffraction data analysis, including phase identification using crystallographic databases (ICSD, PDF-4 or COD), and interpretation of thin-film diffraction data (texture, strain, epitaxy).
• Experience operating laboratory X-ray diffractometers (e.g. Bruker, Rigaku)
• Programming skills like Python for data analysis and automation.
• Clear written and verbal communication skills, with the ability to produce high-quality technical documentation
• PhD (or MSc with significant experience) in Physics, Materials Science, or a related discipline.

The “Nice to haves”:

• Experience with complementary techniques like SEM, AFM, TEM, EDX or alike
• Knowledge of thin film growth models and method
• Experience with synchrotron-based X-ray techniques.
• Familiarity with Rietveld refinement for polycrystalline materials
• Experience applying machine learning techniques to materials data

The ideal candidate will combine strong experimental skills with a deep understanding of diffraction and scattering physics, and the ability to extract meaningful physical parameters from thin-film systems.

Why Join OQC?

At OQC, you’ll work shoulder-to-shoulder with world-class scientists, engineers and technologists who are redefining what’s computationally possible. This is a rare opportunity to apply your materials science expertise to ge]]> <