Area of research: Real-Time Learning from Massive Streams -------------------------------------------------------------------------- General area: Applied Machine Learning / Data Science --------------------------------------------------------------------------- An abundance of data available from both academic and industry fields, as well as cheap computing power, has created an ideal research playground for people with skills in the area of Data Science. This is a hybrid field encompassing Mathematics, Optimization, Databases, Algorithms & Data Structures with a view to bring out innovative solutions to existing problems by exploiting available data, e.g., data produced on the Web or data on our daily human behaviour to optimize our living environments. Focus area: Mining News and Social Streams -------------------------------------------------------------- The wide adoption of social media platforms such as Twitter, Facebook and Youtube has changed the way we produce and consume online content. News stories are currently a mix of curated content by news agencies, as well as citizen-driven content that first breaks and goes viral on social media. Previously, these two types of data (news articles and social media streams) were studied independently of each other, but there is huge potential in tracking and connecting these streams in real-time, in order to enable the flow of information between the two. This research project will focus on investigating methods to meaningfully connect massive news and social media streams in real-time, and build on this connection for solving problems in the area of story tracking and recommendation, summarisation and clustering. Eligibility: ------------- BSc or MSc Degree in Computer Science or Mathematics (strong programming skills required) Essential skills: --------------------- -Background/experience in the area of Machine Learning and/or related fields (Data Mining, Information Retrieval, Statistics, Optimization, Algorithms & Data Structures) -Strong maths and programming skills Desirable skills: --------------------- -Experience developing scalable machine learning models -Experience working on text mining Description of position: ------------------------------- This is a 4 year fully funded PhD position, with a PhD scholarship of euro 18,000 per year (no tax, PhD fees paid). Application procedure: ------------------------------ Informal enquiries about this position can be made to: georgiana.ifrim@insight-centre.org When applying, please use the same email address as above and subject "PhD Position in Real-time Learning from Massive Streams". Candidates are requested to submit a 1 page cover letter and a CV detailing relevant experience and courses with grades (in PDF format). Interviews will be carried out as soon as suitable candidates are identified, and the position needs to be filled as soon as possible. We expect the successful candidate to start at the earliest possible date. Application End Date: ----------------------------- Monday, February 2, 2015
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Posted by: Tri Kurniawan Wijaya <trikurniawanwijaya@yahoo.com>
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