突然收到这么一封邮件……
Dear Zhe Yang,
This is the program committee of MSRA Newsletter / Intern Story Program. Aim of this program is to provide interns a platform to know the colorful intern lives in MSRA and also to show themselves to other people. Selected stories will be published both in MSRA internal platforms and the external platforms, such as the Alumni platform on Renren, newsletter, and blog.
For the current issue, our intern story focus on the topic “How to become an Intern in MSRA”. As recommended by UR group and introduction of your college, we know that you have referred a lot of candidates to MSRA. Therefore, we think you are the special and right intern we are looking for and are well-qualified to write a representative story. Thus, the program committee would like to sincerely invite you to write down your story about how you refer candidates to MSRA and successfully bring them here, which we believe will motive and inspire other interns a lot.
Following is the general structure of the intern story:
1. Brief introduction of yourself: Name, University, research interest and result/award, your current status
2. Your experience of how you refer candidates to MSRA and successfully bring them here
Please list some facts about “how you know the Intern Referral program and the opening intern Positions”, “how you do the intern referral”, “how many candidates you have referred and how many of them successfully come here, please give us some specific examples”, “Do you think intern referral is special and useful”.
3. Other experiences you want to share with us.
4. 1-2 picture of yourself.
It just needs 400 words, both the Chinese version and English version.
肯定会写跑题的。。。。。
—————————-下面是正文———————————–
我是杨哲，来自东北大学软件学院，09级本科生。今年3月开始在MSRA网络多媒体组实习，目前跟随熊志伟研究员做深度测量相关的研究。
其实来这里之前，对微软亚洲研究院的了解不是很多。来这边之后除了发现实习生里女生数量和质量都好于我们系之外，知道一些业绩出色的美国高科技企业会每年投入大量的资金给自己的研究院，即使研究员的成果无法变成产品为公司赢得利润（当然能转化为公司的专利或产品更好）。而这种不强求一定能赚钱、很多时候只需要发牛paper就可以的“业界良心”制度下，拿着高薪的研究员有更大的时间做自己喜欢的研究，也少了很多在高校搞研究不得不面对的麻烦事，科研动力和效率也就高了很多。因此微软等研究院汇聚了世界各地的牛人加入，每年都有大量顶级会议的论文出自微软在世界各地的研究院，作为微软在海外最大的研究院，亚洲研究院，自然也少不了顶级会议的论文，在很多领域的科研能力也超国内各个科研机构与高校。
除了几百名拥有博士头衔的研究员（当然也有特别牛的非博士成为研究员），剩下的就是全国各地乃至海外的实习生。实习生中有很大一部分是以联合培养的形式在这里读博士，研究生第一年在学校上课，之后来MSRA进行四年的科研训练后拿本校的博士学位；另一部分就是通过投简历的形式进行三个月以上的短期实习。因为实习生有权利内推实习生，来这边几个月我也推了一些人，并且有一位成功通过面试成为实习生。因此今天我的主要任务其实是向大家分享关于推荐实习生的经历（其余的可以算题外话了……）。
我一共帮忙内推了五六个人，其中有我的大学同学，也有学CS的高中同学，也有在网上认识的ACMer。成功的是一个ACM/ICPC成绩并不出众的非名校ACMer，我这么说并无贬义，而是想说明MSRA选拔实习生并不是要选择最牛的学校或者竞赛拿到很高的奖，只要能力突出都有机会。
因为不是所有的实习生职位都会公开招聘（一些是联合培养，一些是与高校实验室的导师有合作），因此要把握住公开招聘的机会。一般一旦有某个组放出公开的实习生招聘通知，官网都会第一时间放出消息，所有实习生也会收到邮件鼓励内推，这个时候投简历/推荐同学的成功率肯定最大。对于本科生来说，除了一些可以进入实验室搞研究之外，很多人其实并没有很深入的从事科研，也没有所谓的研究方向，很多领域也还不大了解，甚至自己喜欢做什么、想做什么、适合做什么都不清楚，这种情况下的人很多会倾向于去“热门”的组。在互联网、数据挖掘等领域很火的今天，WSM组实习生职位的竞争程度可想而知。因此对于想来“看一看”，或者还没有过分训练自己的“专长”因而非去某些组不可的时候，倾向于应聘一些非热门组成功率肯定会大一些。这有点像高考的“热门学校冷门专业”。
虽然不太了解招实习生的具体流程和选拔形式，也不知道内推能有多大优势。但总体上有几点我觉得很容易判断，一个是公开招实习生通常是某个项目需要人手，因此比较着急，在这种情况下简历投得越快越好。而且网站上放出的招聘职位是永久的信息，并且精确到人数（而不像校园招聘或长期招聘永久员工那样每年都是那些信息随时可以投简历），没有反馈通知你是否这个职位已经招到人了，因此过了一两个月很有可能投简历就已经意义不大了；还有一点是所有人都希望实习生能多干一段时间，免去不断换人造成的适应时间，所以虽然一般都注明实习期至少三个月到半年，但最好还是能保证实习半年甚至超过半年。另外有一点要注意，实习生一定要是在校生（毕业不能实习，除非延期毕业），研究生来实习也要经过导师同意。
不同研究员的口味不同，简历也许会通过也许会石沉大海，科研项目可能需要科研的背景，如果需要实习生做的是偏工程的工作可能会更侧重项目开发经历。面试总体上可能也是算法为主（据说不少《编程之美》的题或者变种题……），这些都不是临时准备就能快速进步的，都需要一个长期的积累。因此与其研究如何更容易成为某公司的实习生，不如研究如何全面系统的提高自己的能力。当然机遇、运气等也是不可避免的因素，但我们能做就是为那些可控的因素做充分的准备。
最近不常写东西，文笔也大不如从前，很荣幸被约稿写这篇文章，希望对大家有所帮助。
（貌似超字数了。。。。。。。。。。。。。。）
————————-下面是蛋疼菊紧的英文版—————————-
I’m Philo Yang, from Software College, Northeastern University. I’m an intern in Internet Media Group since March this year. My mentor is Zhiwei Xiong, a very kind reseacher 🙂
MSRA was very mysterious for me before. After checking in, I find there are more girls than my college as well as more well-known researchers than most of universities in China. Every year, there are many papers accepted by top conferences and journals.
Besides researchers, there are many interns doing different work. Some interns are in Joint Training Project where they can study research skills for four years and get their own University’s phd degree; others like me are short term internship. Interns can refer candidates to MSRA, so I have referred some students from different universities and one student passed the applying. Today, I will share my referring experience with you.
I have referred 5 or 6 students including my schoolmates from NEU, my high school classmates studying computer science, and some ACMers. The only one success case is an ACMer from un-top school and having no ACM/ICPC prize. The only reason I describe him like this is to show MSRA doesn’t have excessive demands on education background or competition result, as long as you are the suitable one, you will win the offer.
Because not all internship positions are public, if you (or your friends) want to get the offer, once some groups need new interns, you must apply/refer as soon as possible. For undergraduates, many students have no research background and don’t know which group is suitable for him, and many guys will apply some groups on hot areas like data mining even if he is not good at this. So I think if you don’t have a strong desire to one group, you can apply some groups whose competition is relatively intense.
I don’t know the process of selection or the superiority of other interns’ referral. However, I think it is obviously that one public position may mean this group have project which need hands now. So the earlier you cv is sent to the researchers, the greater opportunities you will have. Different researchers have different requirement, someone need students having research experience, while others may need excellent coding skills or algorithm ability. And it’s better if you can be an intern for half an year or longer even if three months is enough because everyone need an adaptation period and frequent replacement of interns will not help researchers more.
No matter how you prepared, the most important thing is “ability”. It can not be gotten in a short time, so you must improve your ability at any time.
Poor English, but I still hope it’s helpful for you.
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