Job Title: Researcher / Assistant Researcher

Full-time/Part-time: Full-time

Number of Hire: 3-6

Work Location: Shanghai

Group Overview:

The MSRA Shanghai research group focuses on key research areas related to machine learning or artificial intelligence, especially deep learning. The group members have published many papers in top-tier conferences and journals in the recent years, e.g., ICML, NIPS, ICLR, KDD, SIGIR, WWW, AAAI, IJCAI, WSDM, CIKM, ICDM, SDM, TKDE, etc. Besides research contributions, the group has also been actively applying cutting-edge AI technologies to real world problems in the industries, e.g., financial services, logistics, healthcare, etc. The AI Quantitative Trading Engine developed by the team has achieved top performance among existing enhanced index funds in China.

Job Description:

-      Conduct state-of-the-art research in areas related to machine learning or artificial intelligence, especially deep learning, including problem formulation, data analysis, algorithm design, algorithm implementation, experimental study, and demonstration. Publish papers in top-tier AI conferences and journals.

-      Transfer cutting-edge AI research to Microsoft products, including prototype implementation and cooperation with engineering team for product implementation.

-      Build world-class AI solutions for local government and other industries, e.g., financial services, logistics, healthcare, etc., to transform their business.

Required Qualifications:

-      Strong motivation to conduct state-of-the-art research work and publish paper in top-tier conferences and journals.

-      Strong implementation skills in at least one of the mainstream programing languages, e.g., Python, C, Java. Implementation experiences with deep learning frameworks, e.g., TensorFlow, PyTorth, Keras, are preferred.

-      Master or Ph.D. candidates major in computer science, statistics or related areas with good English reading/speaking/listening/writing skills.

-      Have published papers in top-tier conferences or journals as first author, e.g., CCF Rank A conferences or journals.

-      Candidates who have research experiences in feature learning, reinforcement learning, non-convex optimization, recommendation algorithm, online advertising are preferred.

Contact: dongsli AT microsoft.com