Cloud Computing Search

Monday, January 19, 2015

Research Associate or Senior Research Associate in UCL Machine Reading Group


Applications are invited for a Research Associate or Senior Research Associate in Statistical Natural Language Processing and Machine Learning to work with Dr Sebastian Riedel (UCL Computer Science).

The overarching goal of this project is to develop reading and reasoning machines that perform tasks which require a deeper understanding of language, such as question answering, automatic fact checking, and passing multiple-choice science exams. Towards this end we will develop methods that integrate scalable and robust matrix/tensor factorization models [1] (and possibly deeper latent models) with expressive symbolic approaches [2]. The project is funded through Riedel's Allen Distinguished Investigator Award [3].

The associate will be part of the UCL Machine Reading lab in the Computer Science department, a rapidly-expanding group located in the Bloomsbury campus in central London. The lab is affiliated with the Centre for Computational Statistics and Machine Learning (bringing together CS, the Gatsby unit and Statistics department). Several close links to relevant industry in London exists (BBC, Google, Microsoft, Google Deepmind), as well as to the vibrant academic NLP scene in the South England area.  

The ideal candidate will have:
* a PhD in Computer Science or Statistics with a focus in machine learning and/or natural language processing,
* presented publications at top ML/NLP conferences (e.g., ACL, NAACL, EMNLP, ICML, NIPS),
* experience with matrix and tensor factorization, graphical models and neural networks,
* strong coding skills and
* the ability to work independently and supervise students

For senior posts the applicant is additionally expected to have experience in leading research projects and developing grant proposals. 

Application Closing Date: 4 Feb 2015
Start Date: March 2015 at the earliest, but there is some flexibility if the perfect candidate needs to start later if necessary.
Duration: the post is funded for 3 years in the first instance.

1 comment: