Research Associate in Topic Modelling and Personalisation

Research Associate in Topic Modelling and Personalisation

Posted by Rebecca Martin on Wed, 10/12/2014 - 13:44

Applications are invited for a postdoctoral research associate to work with Dr Emine Yilmaz on the project “Adaptive User Modelling for Personalized Experience”. The project concerns the development of new models and algorithms to model scientific content in terms of topics/themes and develop novel user interest models based on user’s content engagement activities. The goal is to build adaptive models which incorporate variations in user preferences to deliver personalized experiences in a range of possible practical applications.

Key Requirements:
Candidates should have a PhD (or will shortly be assessed for a PhD) in Computer Science or related areas with a strong background in Machine Learning and/or Information Retrieval or have held a previous postdoctoral position in Bayesian analysis and latent variable modelling, or closely related areas. Experience in at least one of probabilistic graphical models and approximate inference (as demonstrated by a strong publication record), or bayesian nonparametrics is required. Previous experience on personalization techniques and analysing large volumes of data is highly desirable. Previous experience on topic modelling and query log analysis is a big plus.

This post is funded until October 2016 in the first instance.

Full details can be found at http://tinyurl.com/nushszm.