Cambridge Internship Opportunities: Research Intern

Job Description

Over the coming decade, deep learning is 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 AI4Science 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 research project at the intersection of machine learning and chemistry with a focus on retrosynthesis. This is an exceptional opportunity to drive ambitious research in a highly collaborative, diverse and global team of other researchers and engineers, and to push the state of the art in deep learning for the natural sciences.

Responsibilities

· 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 natural sciences.

· Write research code to test new approaches or develop novel insights for machine learning in the natural sciences, particularly retrosynthesis and drug discovery.

· Communicate research findings to an interdisciplinary research team.

· Prepare technical papers, presentations, and open-source releases of research code.

Qualifications

Required/Minimum Qualifications:

· Research experience in deep learning, demonstrated for example through research in a related PhD program and/or publications in ML conferences or scientific journals.

· Hands-on experience with Python and a modern deep learning framework.

Other Requirements:

· Ability to physically work from Microsoft Research Cambridge (UK) for the duration of the internship.

Preferred/Additional Qualifications:

· Published work in the broader field of AI for Science.

· Practical experience with handling molecular data and geometric deep learning.

· Good engineering skills, including familiarity with Git, code reviews, and testing/CI.

· Familiarity with graph algorithms and data structures.

· Effective communication skills, especially scientific writing.

· Desire to tackle real-world problems, and contribute to projects with scope larger than a typical academic publication.

· Chemistry knowledge is a plus, but not required.

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.