Full Time Opportunities, Microsoft Research Residency: Artificial intelligence

[Cheng Zhang]

Application link: Full Time Opportunities, Microsoft Research Residency: Artificial intelligence in Cambridge, Cambridgeshire, United Kingdom | Research at Microsoft

Microsoft Research Cambridge (UK) is looking for an AI residency (fixed-term researcher) in machine learning, focusing on deep generative models and efficient decision-making under uncertainty.  The candidate will closely work with researchers of the Machine Intelligence group and collaborate with other technical and business units in Microsoft in general. The research will involve advancing state-of-the-art machine learning methods to handle real-world heterogeneous data and personalized decision-making for real-world applications in the context of both first-party and third-party collaborations. The role can be considered as a post-doc level role in an industrial research lab.   Thus, it offers a unique opportunity to interact with researchers and product teams alike and develop novel deep learning techniques and apply them in practice.
 
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. For more information about the post, please feel free to email Cheng Zhang at Cheng...@microsoft.com

Contract duration: 2 years. 

Responsibilities
The successful candidate will undertake cutting-edge research on efficient decision making in collaboration with other team members in Microsoft Research. They will write research code to test new approaches or develop novel theoretical and practical insights. They will share their findings with product groups and via publications in recognized academic venues.

Qualifications
Required: 

Completed (or on-track to complete) a PhD in machine learning, deep learning, or a related area, or equivalent experience.  
Track record in relevant research, such as deep generative models, active learning, causal machine learning, as evidenced by publications in top-tier venues. Examples include but are not limited to ICML, NeurIPS, ICLR, AAAI, 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.