[实习]雅虎研发中心【Yahoo!】Intern Scientist for Yahoo! Labs
你是否在寻找一个到跨国公司实习的机会，不仅能够让你学以致用，更让你结识良师益友？你是否渴望加入到充满机会和挑战的团队中，挥洒IT人的青春和汗水？加入我们，与雅虎一起成长，让优秀的我们更加优秀！
核心的产品技术，让你把握互联网前沿脉动
从第一天开始，你就能接触到真实的项目，用自己的工作影响雅虎的业务和全球互联网、移动互联网用户的生活体验。几个月间，你会惊讶于自己的成长速度：
或许你的代码被数以百万计的人使用；
或许是你推出了新的市场活动；
或许是开发出新的产品战略；
又或许是一个惊人的用户界面……
Yahoo! 关注每个实习生的个人成长，无数实习生在这里完成了自己的蜕变，并且正在实现新的梦想，我们相信你也能！
轻松的工作环境，体味地道美式文化
Having fun是雅虎文化重要的一部分：工作累了？想要激发灵感？去玩一玩兵乓球、foosball、Xbox吧，找到和你志同道合的好朋友，来一场酣畅淋漓的比 赛；想喝下午茶？没问题，免费的咖啡、饮料、水果和饼干，绝对让你眼花缭乱！
不仅仅是这些，雅虎还为你提供
亦师亦友的mentor
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和毕业后转为正式员工的机会
——绝对会让你的同学、朋友、室友们羡慕不已！
赶快投递简历，加入雅虎北京团队，踏上一段不同寻常的实习之旅，为你的职业生涯助力！
现在就申请！
发送简历至jobs-bj@yahoo-inc.com，并在邮件正文中标明从何处得到招聘信息。邮件标题：姓名_申请职位_可实习时间_持续实习期。例如：张三_Intern System Engineer_每周四天_连续六个月
要求：1.实习期间为在校学生身份
2.每周至少3天，持续实习4-6个月
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About Yahoo!:
Yahoo! is the premier digital media company. We deliver your world, your way by creating deeply personal digital experiences that keep more than half a billion people connected to what matters most - across devices and around the globe. And it's the Yahoos behind the scenes who make this all possible. We are energetic, idea-driven people who are passionate about shaping the future of the digital world. So if this sounds like you, come show us what you've got.
Think about impacting 1 out of every 2 people online – in innovative and imaginative ways that are uniquely Yahoo! We do just that each and every day, and you could too. After all, it’s big thinkers like you who will create the next generation of the Internet experience for consumers and advertisers across the globe. Now’s the time to show the world what you’ve got. Put your ideas to work for over half a billion people.
Job Location: Beijing, PRC
Contact: jobs-bj@yahoo-inc.com
Prerequisites:
1. Be able to work over 3 days a week for at least 3 months (some positions require at least 6 months).
2. Enrolled as student during the whole internship period.
Intern Scientist for Yahoo! Labs
About Yahoo! Labs,
Do you enjoy solving challenging and complex problems? Are you passionate about dealing with Tega-byte daily data? Do you want to help deliver the best user experience to billions of page views by hundreds of millions of users around the planet every day? Do you like to be the part of the team building one of the most trafficked Internet destinations?
Yahoo! Labs Beijing is the youngest lab in the family of Yahoo! Labs world-wide. Our mission is to improve, revolute, and invent Yahoo's internet products through deep science and technology. We are building world-class teams and expertise on following fields: product-driven sciences; algorithm implementation and optimization in Yahoo! products; large scale research infrastructure; and long-term research and academic relationship.
Some of the prominent research projects we’re working on in the Beijing Labs include:
o Web-scale recommendation: In the post-search era, we are facing the technical challenge of recommending high quality information to correct user, at correct context. Given Yahoo!’s significant strength on web content, we shall make significant efforts towards the solution to web-scale recommender system. There arise quite a few research problems ranging from large scale similarity search, effective user interest modeling, real-time user response optimization to exploration and exploitation mechanism. We are eager to work with talents who are passionate on make the web-scale recommender system alive!
o Social network and data analysis: Social networking sites like Facebook are gaining in popularity in today’s Web. Our research focuses on analyzing the social graphs underlying mail, IM and social networking sites to find influencers, filter out spam, and recommend ads, topics and people to users based on their connections. Another interesting trend on the Web is the rapid growth of user-generated content in the form of blogs, article comments, ratings and reviews, photos, etc. Ranking, summarizing, detecting abuse, and analyzing the sentiment of the vast amounts of user-generated content poses a non-trivial research challenge.
o Computational advertising: The central challenge here is to find the best ad to present to a user engaged in a given context. Selecting an ad which improves the user’s Web-experience while maximizing revenue is a non-trivial challenge. It involves identifying the right audience who may be interested in your product and ready to buy it, quantifying relevance between an ad and its context and predicting click through rates. This being a nascent area, there is tremendous scope for new algorithms that perform and scale better. Our goal is to apply scientific methodology and state-of-the-art technology to display and search advertising to optimize monetization of web traffic.
o Targeting science: Online advertising has been one of the most important ways for Internet monetization. How to find the best match between a given user in a given context and a suitable advertisement is the key problem of computational advertising. Ad targeting seeks to mine the interests, demographic information, and geographic information, etc. of users from web logs and segments users into different groups based on a combination of various user attributes. This involves manipulating web-scale data over large-scale parallel computing platform, investigating massive data and getting insights, applying various data mining techniques to mine valuable knowledge, and delivering results to products, which may impact hundreds of millions of users.
o Natural language processing: Our research aims to set up a content analysis platform which is very important to many Yahoo! products. The tasks include information extraction, named entity recognition, named entity disambiguation, text categorization, ontology, etc. All the tasks are based on Yahoo’s large-scale datasets. We also apply state-of-the-art data mining technology, such as statistical machine learning and topic modeling, to optimize the platform.
o Multimedia search: Increasingly, users of the Web are drawn to interesting multimedia content in the form of images and videos. Flickr alone has a sizable fraction of all the images on the Web. Our research aims to answer questions like: How do we retrieve the most relevant multimedia content taking into account both content features and metadata (e.g., tags)? How do we find similar or related content – across music, image, and video databases – when we have billions of objects?
We are seeking full time interns who help improve develop science solutions to content and collaborative recommendation, user understanding, behavior targeting, query and content analysis, ad selection and ranking, search relevance ranking,.
Required Qualifications:
1. M.S. or PhD candidate in Computer Science, Electronic Engineering, Automation, Mathematics or related fields.
2. Good programming skills using one of C/C++/Java or Matlab.
3. Excellent analytical and problem solving skills.
4. Good communication and teamwork spirit.
Preferred Qualifications:
1. Solid understanding of Machine Learning, Information Retrieval, Data Mining, Natural Language Processing or Computational Optimization.
2. Fluent in a scripting language such as Python, Perl, or UNIX shell.
3. Prior exposure to Hadoop and distributed programming.
4. 4 ~ 6 month full-time availability.
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