Over the coming decade, deep learning will 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 AI4Science team encompasses world experts in machine learning, computational chemistry, material science, quantum physics, molecular biology, fluid dynamics, software engineering, and other disciplines, who are working together to tackle some of the most pressing challenges in this field.
We are seeking interns to join our generative model for materials design team and contribute to a program of research at the intersection of machine learning and materials science.
Responsibilities
You will be embedded in a collaborative ambitious project using deep learning to push the frontiers of generative models for materials design.
Qualifications
Required Qualifications
- Must be currently enrolled in a PhD program in a STEM field.
- Interns are expected to be physically located in their manager's Microsoft worksite location (Cambridge, UK; or Berlin, Germany) for the duration of their internship.
Preferred Qualifications
A subset of the following:
- Understanding and hands-on research experience in machine learning or computational materials science demonstrated for example through research in a PhD program.
- Publications in relevant conferences (e.g. NeurIPS, ICML, ICLR), or high-profile scientific journals.
- Ability to code in Python, as well as familiarity with Git and code reviews.
- Interest in applying machine learning to scientific research.
- Ability to work in an interdisciplinary collaborative environment with people from different technical backgrounds.
The length of this internship is 12 weeks.
