德国 Max Planck Institute (马普所) 计算机与光网络 全奖PhD/Postdoc
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德国马克斯·普朗克研究所（马普所）夏亦婷导师欲招收一名光网络方向博士后及一名计算机网络与系统方向博士。夏亦婷导师博士毕业于美国莱斯大学，现于马普所担任助理教授，从事网络与云计算方面的研究。她曾在美国Facebook公司任研究员，拥有丰富的实践经验，并与企业有着广泛合作。目前她的研究致力于为支撑机器学习和物联网的下一代云计算提供高性能的网络与软件系统。她曾在SIGCOMM, INFOCOM, ICNP, HotNets等国际顶尖会议上发表十余篇论文。请访问 sites.google.com/view/yitingxia 了解更多导师信息。
马普所是德国最负盛名的国立研究院，在基础科学、应用科学、社会科学领域均处于世界领先地位，如仅2020年诺贝尔获奖者中就有两人来自马普所。马普所长期与欧洲和美国的顶尖高校和研究机构保持密切的学术合作，毕业生遍布欧洲和美国的学术界与包括硅谷、苏黎世、慕尼黑、伦敦在内的高科技公司。该项目纯英语教学，无德语要求。博士后与博士均为全职工作，享受全额资金支持，即免学费、优厚的薪资待遇、以及社会福利。德国政治稳定、科技先进、社会制度发达、移民政策友好，是留学的不二之选。该职位所在的萨尔布吕肯市（Saarbrücken）位于德国西部的科技中心，毗邻法国，正处欧洲中部，与诸多世界级旅游胜地仅几小时车程（如距巴黎2小时、法兰克福1.5小时、卢森堡1.5小时、苏黎世3.5小时等等），周围另有一众风景优美的小镇，是周末旅行的好去处。
关于新冠：马普所出台了一系列应对新冠期间签证和旅行困难的措施。目前招聘的两个职位均可随时入职，并支持远程工作。博士后合同可立即开始。博士生如在学年开始之前入职，可先以研究工程师身份开始工作（全职，享受正常工资和社会福利），待到下一学年转成博士生，所做工作可进入毕业论文，毕业时间不会推迟。
职位具体要求如下，请有兴趣者发送英文简历至1point3acres.com进行申请。
Position 1: postdoctoral researcher on optical networking
The traditional data center network based on electrical switches cannot keep up with the growth of cloud traffic due to the fundamental limits on port density and power consumption. We aim to explore alternative data center network architectures using optical switching technologies. Our ongoing projects involve the design of optical network interconnects and switch fabric for intra- and inter- data center communications. The candidate should have deep understanding and hands-on experience with optical components and systems, being able to build optical testbeds to prototype the designs. Knowledge about communication networks is a big plus. There are opportunities to work with Facebook and Huawei, which are our project partners. Depending on the interests of the candidate, there are also opportunities to drive research directions, mentor students, and apply for research grants.
Position 2: PhD student on computer network and systems
The landscape of cloud computing is evolving rapidly driven by emerging applications such as machine learning and IoT. It is time to rethink the design of cloud systems to support these applications. We are interested in exploring two directions: (1) cross-layer design of data center networks and cloud systems to accelerate distributed machine learning; and (2) leveraging programmable network components, such as programmable switches and smart NICs, to enable better performance and manageability of the cloud infrastructure. The candidate should have taken some courses related to computer systems and have strong programming skills to implement distributed systems. Knowledge about machine learning is a plus.
马普所是德国最负盛名的国立研究院，在基础科学、应用科学、社会科学领域均处于世界领先地位，如仅2020年诺贝尔获奖者中就有两人来自马普所。马普所长期与欧洲和美国的顶尖高校和研究机构保持密切的学术合作，毕业生遍布欧洲和美国的学术界与包括硅谷、苏黎世、慕尼黑、伦敦在内的高科技公司。该项目纯英语教学，无德语要求。博士后与博士均为全职工作，享受全额资金支持，即免学费、优厚的薪资待遇、以及社会福利。德国政治稳定、科技先进、社会制度发达、移民政策友好，是留学的不二之选。该职位所在的萨尔布吕肯市（Saarbrücken）位于德国西部的科技中心，毗邻法国，正处欧洲中部，与诸多世界级旅游胜地仅几小时车程（如距巴黎2小时、法兰克福1.5小时、卢森堡1.5小时、苏黎世3.5小时等等），周围另有一众风景优美的小镇，是周末旅行的好去处。
关于新冠：马普所出台了一系列应对新冠期间签证和旅行困难的措施。目前招聘的两个职位均可随时入职，并支持远程工作。博士后合同可立即开始。博士生如在学年开始之前入职，可先以研究工程师身份开始工作（全职，享受正常工资和社会福利），待到下一学年转成博士生，所做工作可进入毕业论文，毕业时间不会推迟。
职位具体要求如下，请有兴趣者发送英文简历至1point3acres.com进行申请。
Position 1: postdoctoral researcher on optical networking
The traditional data center network based on electrical switches cannot keep up with the growth of cloud traffic due to the fundamental limits on port density and power consumption. We aim to explore alternative data center network architectures using optical switching technologies. Our ongoing projects involve the design of optical network interconnects and switch fabric for intra- and inter- data center communications. The candidate should have deep understanding and hands-on experience with optical components and systems, being able to build optical testbeds to prototype the designs. Knowledge about communication networks is a big plus. There are opportunities to work with Facebook and Huawei, which are our project partners. Depending on the interests of the candidate, there are also opportunities to drive research directions, mentor students, and apply for research grants.
Position 2: PhD student on computer network and systems
The landscape of cloud computing is evolving rapidly driven by emerging applications such as machine learning and IoT. It is time to rethink the design of cloud systems to support these applications. We are interested in exploring two directions: (1) cross-layer design of data center networks and cloud systems to accelerate distributed machine learning; and (2) leveraging programmable network components, such as programmable switches and smart NICs, to enable better performance and manageability of the cloud infrastructure. The candidate should have taken some courses related to computer systems and have strong programming skills to implement distributed systems. Knowledge about machine learning is a plus.
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