微软亚洲研究院、微软雷德蒙研究院联合推出的“星跃计划”第二轮报名正在进行中！“星跃计划”首轮报名一经推出，便收到海内外学子的积极报名与热情关注，目前部分项目招募名额已满，本篇推送内的项目还有少量剩余名额。还在等什么？加入“星跃计划”，和我们一起跨越重洋，探索科研的更多可能！该计划旨在为优秀人才创造与微软全球两大研究院的研究团队一起聚焦真实前沿问题的机会。你将在国际化的科研环境中、在多元包容的科研氛围中、在顶尖研究员的指导下，做有影响力的研究！目前还在招募的跨研究院联合科研项目覆盖计算机系统与网络、智能云等领域。研究项目如下：High-performance Distributed Deep Learning, Intelligent Power-Aware Virtual  Machine  Allocation。

星跃亮点

同时在微软亚洲研究院、微软雷德蒙研究院顶级研究员的指导下进行科研工作，与不同研究背景的科研人员深度交流
聚焦来自于工业界的真实前沿问题，致力于做出对学术及产业界有影响力的成果
通过线下与线上的交流合作，在微软的两大研究院了解国际化、开放的科研氛围，及多元与包容的文化

申请资格

本科、硕士、博士在读学生；延期（deferred）或间隔年（gap year）学生
可全职在国内工作6-12个月
各项目详细要求详见下方项目介绍

还在等什么？
快来寻找适合你的项目吧！

High-performance Distributed Deep Learning

The parallel and distributed systems are the solution to address the ever-increasing complexity problem of deep learning trainings. However, existing solutions still leave efficiency and scalability on the table by missing optimization opportunities on various environments at industrial scale.

In this project, we’ll work with scientists who are at the forefront of system and network research, leveraging the world-leading platforms to solve system and networking problems in parallel and distributed deep learning area. The current project team members, from both MSR Asia and MSR Redmond labs, have rich experience contributing to both industry and academic community through transferring innovations that support production systems and publications at top conferences.

Research Areas

System and Networking, MSR Asia
https://www.microsoft.com/en-us/research/group/systems-and-networking-research-group-asia/

Research in Software Engineering, MSR Redmond
https://www.microsoft.com/en-us/research/group/research-software-engineering-rise/

Qualifications

• • Major in computer science, electrical engineering, or equivalent field
  • Solid knowledge of data structure/algorithm
  • Familiarity with Python, C/C++ and other programming languages, familiar with Linux and development on Linux platform
  • Good communication and presentation skills
  • Good English reading and writing ability, capable of system implementing based on academic papers in English, capable of writing English documents

Those with the following conditions are preferred:

• • Familiarity with deep learning systems, e.g., PyTorch TensorFlow, GPU programming and networking
  • Familiarity with NCCL, MPI communication protocols such as OpenMPI and MVAPICH
  • Rich knowledge of machine learning and machine learning models
  • Familiarity with engineering process as a strong plus
  • Active on GitHub, used or participated in well-known open source projects

Intelligent Power-Aware Virtual  Machine  Allocation

As one of the world-leading cloud service providers, Microsoft Azure manages tens of millions of virtual machines every day. Within such a large-scale cloud system, how to efficiently allocate virtual machines on servers is critical and has been a hot research topic for years. Previously, teams from MSR-Asia and MSR-Redmond have made significant contributions in this area that resulted in production impact and publication of academic papers at top-tier conferences (e.g., IJCAI, AAAI, OSDI, NSDI). In this project we intend to unify the strength of MSR-Asia and MSR-Redmond for performing forward-looking and collaborative research on power management in datacenters, including power-aware virtual machine allocation. The project involves developing power prediction models by leveraging the start-of-the-art machine learning methods, as well as building efficient and reliable allocation systems in large-scale distributed environments.

Research Areas

Data, Knowledge, and Intelligence (DKI), MSR Asia
https://www.microsoft.com/en-us/research/group/data-knowledge-intelligence/

System, MSR Redmond
https://www.microsoft.com/en-us/research/group/systems-research-group-redmond/

Qualifications

• Currently enrolled in a graduate program in computer science or equivalent field
• Good research track record in related areas
• Able  to carry out research tasks  with  high  quality
• Good communication and presentation skills in written and oral English
• Knowledge and experience in machine learning, data mining and data analytics are preferred
• Familiarity with AIOps or AI for systems is a strong plus

申请方式

符合条件的申请者请填写下方申请表：
https://jinshuju.net/f/LadoJK
或扫描下方二维码，立即填写进入申请！