Postdoctoral fellowship in distributed graph data analytics at the University of Waterloo and IBM R&D Canada.

We are seeking a Postdoctoral Fellow for a SOSCIP-funded project on Distributed and Scalable Search in Enterprise Databases.  The aim of the project is to build a distributed graph keyword search system on top of Apache Spark GraphX.  The length of the project is two years, with an initial one-year term.  This is a collaborative project between the University of Waterloo and the IBM Canada R&D Lab in Toronto, Ontario. 

Qualifications: The successful candidate will design and develop novel analytical frameworks, infrastructure and algorithms to handle very large graphs.  The project is expected to lead to publications in top-tier venues.  Candidates must have a Ph.D. in Computer Science (or a related field), with a specialization in in large-scale data management, data mining or machine learning, and with a strong publication record.  Expertise in programming languages such as Java, C++ and Python is desirable. Experience with graph databases and distributed environments (e.g., Apache Spark) is a plus. Candidates should have strong communication skills and be able to mentor junior graduate students.

How to apply: The starting date is flexible and applications will be accepted until the position is filled.  To receive full consideration, please send a CV and contact details of three references to Lukasz Golab (lgolab@uwaterloo.ca) by October 25th 2017.