Overview
Over the coming decade, deep learning looks set to have a transformational impact on the natural sciences. The consequences are potentially far-reaching and could dramatically improve our ability to model and predict natural phenomena over widely varying scales of space and time. Our team encompasses world-leading experts in machine learning, computational chemistry, material science, quantum physics, molecular biology, software engineering, and other disciplines, who are working together to tackle some of the most pressing challenges in this field.
We are seeking an intern to contribute to a program of research at the intersection of reinforcement learning and chemistry. This is an exceptional opportunity to drive ambitious research in a highly collaborative, diverse and global team of other researchers and engineers, to push the state of the art in deep learning for the natural sciences.
Qualifications
Required Qualifications:
1. Understanding and research experience in machine learning and/or reinforcement learning, demonstrated for example through research in a related PhD program and/or publications in ML conferences or scientific journals.
2. Interns are expected to be physically located in their manager's Microsoft worksite location for the duration of their internship.
3. Demonstrable understanding and hands-on experience in using deep learning frameworks.
Preferred Qualifications:
4. Practical experience working with deep learning frameworks and scientific data.
5. Ability to write good quality code in Python, as well as familiarity with Git and code reviews.
6. Desire to see research have real-world impact.
7. Demonstrable ability to work and learn in an interdisciplinary collaborative environment, evidenced by effective communication of technical concepts to people from different technical backgrounds.
8. Good communication skills.
Responsibilities
9. Contribute to a high-impact research agenda within the context of a highly collaborative research culture alongside a team of experts in machine learning and scientific research.
10. Write robust machine learning research code to test new approaches or develop novel theoretical and practical insights for machine learning in the natural sciences.
11. Communicate research findings to an interdisciplinary research team.
12. Prepare technical papers, presentations, and open-source releases of research code.
Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.Industry leading healthcareEducational resourcesDiscounts on products and servicesSavings and investmentsMaternity and paternity leaveGenerous time awayGiving programsOpportunities to network and connect