We are seeking a researcher with expertise in materials research (simulation) to work on data storage applications.
This is a two-year fixed-term post-doctoral position and is part of our Cambridge Residency programme within the Cloud Systems Futures research group. The Project Silica team is researching a revolutionary new technique to store data in glass using lasers, and read it using optical imaging, and our multi-disciplinary team innovates in all fields from the materials science to the cloud architecture.
We are looking for a computational materials expert who can work in collaboration with Generative AI experts to apply revolutionary approaches in materials generation and exploration to the search for materials suitable for data storage applications. The successful candidate will work on developing and applying theoretical, computational, and machine learning methods to understand and predict the properties of materials for data storage applications.
Responsibilities
- Conduct research on materials for data storage applications.
- Develop and apply computational methods to predict the properties of materials.
- Actively work with other disciplines to inform and collaborate on research goals.
Qualifications
Required qualifications
- PhD in Materials Science, Physics, Chemistry, or a related field, or equivalent training and experience in research.
- Strong background in theoretical and computational methods of material science or chemistry.
- Experience developing DFT and TD-DFT workflows.
- Strong software development skills (e.g. in Python).
- Excellent written and verbal communication skills.
- Ability to work independently and as part of a cross-disciplinary team.
Preferred qualifications
- Experience of simulating long-range periodic lattices, defects, in lattices, and / or large organic molecules.
- Experience extracting optical properties from simulation workflows.
- Knowledge of machine learning methods.
- Knowledge of material informatics / chemometrics / cheminformatics.
- Experience of developing high throughput simulation workflows, like Atomate, AiiDA.
- Knowledge of experimental methods for material characterization.
- Deep understanding of material properties, light-matter interactions, and photoexcitation dynamics from the first principle.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form.
Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.
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