Cambridge Residency Programme – Microsoft Uk Jobs Sheffield

Overview

Position Title: Cambridge Residency Programme

Company: Microsoft

Location: Sheffield, UK

Job Description

Microsoft Research works with the world’s best researchers, moving with the current of technology as it rapidly evolves. Together we share the motivation to seek innovative solutions to the world’s toughest challenges and improve the lives of people everywhere.

Microsoft Research Cambridge (UK) is looking for an AI resident (fixed-term researcher) in causal machine learning. The candidate will work closely with researchers of the Causal AI team and collaborate with other technical and business units in Microsoft in general. The research will involve advancing state-of-the-art causal machine learning methods including but not limited to causal discovery, causal inference, causal deep learning for real-world applications in the context of both first-party and third-party collaborations. This role offers a unique opportunity for post-doctoral research in novel causal AI techniques with the ability to apply them to some of the most widely used software in the world.

There is no closing deadline for this post. The post will be filled once suitable candidates are found so if you are interested, please apply as soon as possible. When submitting your application, include your CV with a list of publications as an attachment. You may also include your published work.

Responsibilities:

• The successful candidate will undertake cutting-edge research on causal machine learning with other team members including Cheng Zhang, Nick Pawlowski, Stefan Bauer, Chao Ma, Adam Foster, Amit Sharma, Emre Kiciman, Eleanor Dillon and others in Microsoft Research.
• They will write research code to test new approaches or develop novel theoretical and practical insights and test these new approaches on real-world data.
• They will share their findings with product groups and via publications in recognized academic venues.

Requirements:

• equivalent experience.
• Track record in relevant research, such as causal machine learning, deep generative models as evidenced by publications in top-tier venues. Examples include but are not limited to ICML, NeurIPS, UAI, AIStats, etc.
• Hands-on experience with current deep learning frameworks (PyTorch, TensorFlow, etc.), as evidenced by released code (e.g. on GitHub or elsewhere).
• Software engineering skills for rapid and accurate development.
• Effective communication skills and ability to work in a collaborative environment.