以下是网站 videogeometry.com 在 2014-12 的历史页面存档,小提示:CTRL+U 查看源码
本站和 videogeometry.com 的作者无关,不对其内容负责。本历史页面谨为网络历史索引,不代表被查询网站的即时页面。 *号[x]表示已屏蔽显示的敏感字。
原网页标题:VideoGeometry.com – DeepMetadata.tv – RecSys.tv – Jan Neumann | Data Science, Machine Learning and Computer Vision for a better TV Experience

Comcast Labs DC is looking for 4-5 Graduate Student Summer Interns

Are you interested in Large-scale Machine Learning? Multimedia Video Processing? Working with truly Big Data? Do you currently do research in at least one or more of the following areas – Large-scale Machine Learning, Recommendation Systems, Social Media, Computer Vision, Information Retrieval or NLP? Do you want to conduct industry-leading research in content discovery technologies and multimedia information processing, and help millions of households discover video and music content on their TV, PC, Phone, and Mobile devices?

Comcast Labs in Washington DC is currently looking to fill 4-5 graduate student intern positions for this summer (minimum of 12 weeks, May through September). Projects can focus on using Statistical Modeling of TV Viewing Behaviors, Personalized Recommendations for TV, and Search, Annotation, and/or Segmentation of premium video.

We are an innovative research group within Comcast’s Metadata Processing and Search Services unit that does groundbreaking research to develop the video and TV search & discovery technologies that support Comcast’s approximately 22 Million subscribers.

Comcast is the largest provider of TV and Broadband Services in North America, the largest provider of TV search and discovery applications in North America, & the 6th largest provider of search on the web.

The ideal applicant will be currently enrolled in a university PhD program and has 2+ years of research experience in one of the relevant areas. Applicants should also have good programming and software development skills, and be comfortable working in an interdisciplinary, team-oriented, applied research environment.

Internships will be on-site in our Washington, DC office. We feature an informal, open atmosphere, and a location in downtown Washington convenient to several public transit lines and many of the city’s museums, monuments, and other attractions. The salary is competitive and commensurate with experience.

To apply, please send a CV or resume, along with a brief statement explaining why you are interested in the position, to Jan_Neumann(at)cable.comcast.com. While there is no fixed deadline for applying, we anticipate filling these positions by the end of February.

 

 

Comcast Labs DC is looking for 2 Senior Researchers in Machine Learning, Computer Vision and/or NLP

Are you interested in solving problems that involve massive data sets and improve the experience of millions of people? Do you have experience in at least one or more of the following areas – Large-scale Machine Learning, Recommendation Systems, Social Media, Computer Vision, Information Retrieval or NLP? Do you want to conduct industry-leading research in content discovery technologies and multimedia information processing, and help millions of households discover and enjoy video and music content on their TV, PC, Phone, and Mobile devices?

Comcast Labs in Washington DC is currently looking to fill 2 senior researcher positions that require research and prototype development in one or more of the following areas: Statistical Modeling of TV Viewing Behaviors, Personalized Recommendations, Knowledge Graphs and Computer Vision/Video Processing applied to premium video and home security. The ideal candidate will have experience working in an industrial, government, or academic lab setting and applicants with Masters or PhD are strongly preferred.

We are an innovative research group within Comcast’s Metadata Products and Search Services unit that does groundbreaking research to develop Search & Discovery technologies for Video and TV that support Comcast’s approximately 22 Million subscribers. Comcast is the largest provider of TV and Broadband Services in North America, the largest provider of TV search and discovery applications in North America, & the 6th largest provider of search on the web.

The ideal applicant will have a Master’s or Ph.D. Degree along with research experience in one of the relevant areas. Applicants should also have good programming and software development skills, and be comfortable working in an interdisciplinary, team-oriented, applied research environment.

The positions will be located in our Washington, DC office. We feature an informal, open atmosphere, and a location in downtown Washington convenient to several public transit lines and many of the city’s museums, monuments, and other attractions. The salary is competitive and commensurate with experience.

To apply, please send a CV or resume, along with a brief statement explaining why you are interested in the position, to Jan_Neumann(at)cable.comcast.com.

 

Core Responsibilities:
– Develops specifications and technical requirements of custom designs for future products and applications.
– As Sr. Researcher responsible for leading Research in one or more of the following areas: Information Retrieval, Machine Learning, Natural Language Processing, Data Mining, and Image/Video Processing.
– Works with Technical Leads, Product Managers and Business Partners to build prototypes that demonstrate Research work and help with Product Discovery.
– Works with various team members both within and outside Research. Ensures timely progress of work. Conducts Research in an incremental manner thereby enabling faster transfer of technology to the Engineering teams. Able to evaluate prototype systems, help write technical papers, and help with technology transfer.
– Keeps track of developments in field both in academia and in industry. Attending relevant conferences and publishing research results is encouraged.
– Other duties and responsibilities as assigned. Regular, consistent and punctual attendance. Must be able to work nights and weekends, variable schedule(s) as necessary.

Education Level: Bachelor’s Degree or Equivalent; Masters or Ph.D. strongly preferred.
Field of Study: Computer Science with experience in one or more of the following areas Information Retrieval, Machine Learning, Natural Language Processing, Computer Vision, Video Processing
Years of Experience: Generally requires 5-8 years related experience after Bachelors, 2-3 years after Master’s, or a fresh Ph.D.
Compliance: Comcast is an EEO/AA/Drug Free Workplace.
Disclaimer: The above information has been designed to indicate the general nature and level of work performed by employees in this role. It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities and qualifications

1st Workshop on Recommendation Systems for TV and Online Video (RecSysTV 2014)

Together with Danny Bickson (GraphLab), John Hannon (Boxfish) and Hassan Sayyadi (Comcast Labs DC) I am organizing the First  Workshop on Recommendation Systems for Television and Online Video (RecSysTV) on October 10th, 2014, as part of the 2014 RecSys conference. Please check out the workshop web page for more information about the topic and the exciting program. We hope to see you there!

Talk on Popularity Prediction of TV Shows at NCTA Technical Forum

I presented a talk at the yearly meeting of the National Cable and Television Association (NCTA) on how to combine TV usage statistics with social signals such as Twitter for improved popularity prediction of TV Shows. Here is the link to the paper. (Also, see here for an interesting take on our use of random forests :-) http://www.multichannel.com/blog/translation-please/best-ncta-s-tech-papers-part-2/373214)

2010 Summer Workshop of the Center for Language and Speech Processing

During the summer of 2010 I led a research team at the 2010 Summer Workshop of the Center for Language and Speech Processing at Johns Hopkins University. For 6 weeks we worked on combining text and video analysis to identify and localize complex actions in broadcast videos. You can find more detailed information about our project and our results here.