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。
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
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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.
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/
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.
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/
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
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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！
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