The Department of Computer Science has a vacancy for a PhD-position in
mining streaming data, in a project funded by DNB (Norway’s largest
financial services group) and NTNU. The project’s focus is on
technologies and architectures for dealing with large-scale real-time
data processing, with emphasis on solving business challenges within
the banking and finance sector.

In the financial sector, a wide range of data sources can be used both
to understand customers, as well as the financial market in
general. These data sources may contain both structured data (from
typical financial services), as well as textual data (from
communication with users, news media, or social media). Common for
much of the interesting data, is that it is in the form of data
streams that needs to be processed in real-time. The topic of this PhD
position is effective information analysis (i.e., querying, searching
or mining) on such data streams.

Much of the data relevant for financial services has either an
implicit or explicit time dimension, and often also a geographical
aspect. The PhD student will develop techniques for effective
information analysis on such data, in one of the following areas
(depending on interest and background of the candidate):

-Algorithmic: Scalable algorithms for retrieval and mining of
spatio-temporal streaming data
-Information retrieval: Searching and mining spatio-temporal-textual
streaming data




Relevant background: A solid knowledge of database systems,
algorithms, data mining or information retrieval is essential, and a
research-oriented master thesis within one of these or related areas
are expected. Good programming skills are required. An ability/desire
to publish in top academic conferences (VLDB, SIGMOD,
ICDE, KDD, ICDM, CIKM, SIGIR, etc.) is essential.

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