Overview
This is a 24‑month fixed‑term post‑doctoral Residency within the Future AI Infrastructure group at Microsoft Research Cambridge (UK), contributing to the Materials for the Cloud project. The role sits at the interface of machine‑learning‑accelerated materials discovery and experimental materials science, focused on the synthesis and characterisation of novel thin‑film materials for future AI cloud infrastructure. You will work within a team with full‑stack capability, spanning first‑principles computational simulation through experimental synthesis and characterisation to application‑specific engineering, in close collaboration with researchers across materials science, AI for Science, optics, electronics, and machine learning.
The successful candidate will design, fabricate, and characterise thin‑film materials, translating computational insights into experimentally validated prototypes. You will operate in a fast‑moving research environment while maintaining a rigorous and systematic approach to experimental design and debugging of physical systems. This role suits a detail‑oriented, open‑minded experimentalist with strong foundations in materials physics, thin films, and optics, motivated to develop next‑generation materials that improve the cost, performance, and sustainability of AI cloud infrastructure.
Responsibilities
- Design and execute thin-film deposition experiments using physical vapour deposition (PVD) techniques to fabricate functional materials.
- Characterise deposited films using a suite of analytical tools, such as X-ray fluorescence (XRF), X-ray diffraction (XRD), transmission electron microscopy (TEM), scanning electron microscopy (SEM), Ellipsometry, and atomic force microscopy (AFM).
- Development of Machine Learning driven approaches to automation of experimental materials synthesis and characterisation
- Collaborate across disciplines, including chemistry, physics, computer science, and machine learning, and contribute to joint research efforts with internal partners.
- Contribute to the presentation of research findings, in internal meetings or reports, or towards the preparation of submissions to peer-reviewed journals.
- Maintain and troubleshoot vacuum systems and diagnostic equipment, ensuring reliable operation of sputtering tools and characterisation equipment.
Qualifications
Required:
- PhD in Engineering, Materials Science, Physics, or a related field, or equivalent training and experience in research.
- A demonstratable record working at the interface of different research fields - especially materials and optics.
- Experienced in physics of materials and their interaction with light.
- Strong analytical skills and experience in data recording, processing and interpretation.
- Ability to work independently and collaboratively in interdisciplinary teams.
- Excellent communication skills in English, both written and spoken.
Preferred Qualifications:
- Knowledge and background in thin-film growth methods.
- Hands-on experience with physical vapor deposition systems for thin film fabrication.
- Hands-on experience with X-ray fluorescence (XRF), X-ray diffraction (XRD), transmission electron microscopy (TEM), scanning electron microscopy (SEM), Ellipsometry, and atomic force microscopy (AFM).
- Hands-on experience with optical lab components and instruments (e.g., lasers, free-space assemblies, optical microscopy systems).
- Experience designing and using free-space optical systems.
- Ability to program in Python.
- Knowledge of machine learning approaches for materials analysis or process optimisation.
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about **requesting accommodations.**