This is a 12-week fixed-term Research Intern position within the Future AI Infrastructure research group at Microsoft Research Cambridge (UK), as part of our “Materials for the Cloud” project to improve the cost, performance or sustainability of future AI cloud infrastructure. This is a unique opportunity for a student researcher with experimental skills in materials synthesis and characterisation, thin films, and optics to design, fabricate and characterise novel materials for future AI infrastructure.
The ideal candidate will have a can-do and open-minded attitude and be prepared to work within a rapidly changing research environment, while simultaneously taking a rigorous and systematic approach to design, implementation and debug of physical systems with a high attention to detail.
You will be tasked to use your breadth of knowledge in materials physics, thin-films, and optics to develop techniques to design and prototype next generation materials for cloud infrastructure applications. You will be required to envisage, design, and model new thin-film materials, and then validate these designs by experimentally fabricating and characterising their properties.
You will work with researchers in materials, optics, electronics, machine learning and computer science, feeding back results and experience as well as learning about, considering, and understanding the additional constraints to find good solutions to difficult problems.

QUALIFICATIONS

Required:

• Undergraduate or Master level degree in physics, materials science, or a closely related field.
• Currently enrolled in a PhD program with at least 12 months experience researching materials.
• 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 (zero or more of):

• Knowledge and background in thin-film growth methods.
• Hands-on experience with physical vapor deposition systems for thin film fabrication.
• Hands-on experience with optical lab components and instruments (e.g., lasers, free-space assemblies, optical microscopy systems).
• Experience in atomistic (e.g. DFT) and electromagnetic (e.g. FDTD) modelling.
• Experience designing and using free-space optical systems.
• Ability to program in Python.
• Knowledge of machine learning approaches or materials analysis or process optimisation.

Microsoft is an equal opportunity employer. Consistent with applicable law, 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 and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations

Specific responsibilities during the internship may include:

• 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), X-ray photoelectron spectroscopy (XPS), transmission electron microscopy (TEM), scanning electron microscopy (SEM), Raman, and atomic force microscopy (AFM).
• 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 machines and characterisation instruments.