Internship opportunities at Twitter Cortex
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Hugo
Dec 6, 2015, 11:04:25 AM12/6/15
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PhD Intern Call - Twitter Cortex
Application Deadline: 01/31/2016
Twitter Cortex, the deep learning / machine learning arm of Twitter, is offering internships for the summer of 2016. Twitter Cortex is tasked with the development of machine learning models and representations applicable to all Twitter data: tweets, images, video, users and their interaction, etc. See https://cortex.twitter.com for more information on our group.
Internships aim to nourish the candidate’s research career in the context of Twitter’s challenges. The intern’s project will ideally build and expand upon the candidate’s own work, through collaborations with Twitter’s own machine learning researchers. A successful internship will result in not only the successful implementation and execution of an idea for Twitter’s data, but also a preliminary draft of what could become a scientific publication in an international conference. Internships run for a duration of 12 weeks, from June to August 2016, and depending on the specific project, will be located at Twitter’s New York, Cambridge or San Francisco office.
We are seeking candidates with strong expertise in deep learning, graphical modeling, Bayesian learning, optimization, computer vision, natural language processing or other related disciplines. We ask that candidates submit a 2-page proposal outlining a project they’d like to work on during their internship. Examples of topics that are of interest to Twitter Cortex are listed below.
Applications
- Image modeling (classification, captioning, question answering, etc.)
- Video modeling (classification, captioning, etc.)
- Tweet modeling (text embeddings, conversation modeling, etc.)
- Social network modeling (user embeddings, user relation modeling, etc.)
Methods
- Deep learning architectures (recurrent, attentional, memory networks, etc.)
- Bayesian learning and uncertainty modeling with neural networks
- Distributed optimization algorithms
- Active learning, online learning, zero-shot learning
- Bayesian optimization
The proposal should highlight the relation between the project and the candidate’s expertise and current research.
In addition, candidates should provide a resume and the contact information for 2 references that can speak to the candidate’s abilities and strengths.
Complete applications or questions about the program should be sent to cortex-in...@twitter.com.
Hugo Larochelle
Research Scientist
Twitter Cortex
Application Deadline: 01/31/2016
Twitter Cortex, the deep learning / machine learning arm of Twitter, is offering internships for the summer of 2016. Twitter Cortex is tasked with the development of machine learning models and representations applicable to all Twitter data: tweets, images, video, users and their interaction, etc. See https://cortex.twitter.com for more information on our group.
Internships aim to nourish the candidate’s research career in the context of Twitter’s challenges. The intern’s project will ideally build and expand upon the candidate’s own work, through collaborations with Twitter’s own machine learning researchers. A successful internship will result in not only the successful implementation and execution of an idea for Twitter’s data, but also a preliminary draft of what could become a scientific publication in an international conference. Internships run for a duration of 12 weeks, from June to August 2016, and depending on the specific project, will be located at Twitter’s New York, Cambridge or San Francisco office.
We are seeking candidates with strong expertise in deep learning, graphical modeling, Bayesian learning, optimization, computer vision, natural language processing or other related disciplines. We ask that candidates submit a 2-page proposal outlining a project they’d like to work on during their internship. Examples of topics that are of interest to Twitter Cortex are listed below.
Applications
- Image modeling (classification, captioning, question answering, etc.)
- Video modeling (classification, captioning, etc.)
- Tweet modeling (text embeddings, conversation modeling, etc.)
- Social network modeling (user embeddings, user relation modeling, etc.)
Methods
- Deep learning architectures (recurrent, attentional, memory networks, etc.)
- Bayesian learning and uncertainty modeling with neural networks
- Distributed optimization algorithms
- Active learning, online learning, zero-shot learning
- Bayesian optimization
The proposal should highlight the relation between the project and the candidate’s expertise and current research.
In addition, candidates should provide a resume and the contact information for 2 references that can speak to the candidate’s abilities and strengths.
Complete applications or questions about the program should be sent to cortex-in...@twitter.com.
Hugo Larochelle
Research Scientist
Twitter Cortex
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