949Postdoc position -- Machine Learning and Data Mining (Netherlands)
- Dec 12, 2013+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Postdoc position -- Machine Learning and Data Mining
Maastricht University, The Netherlands
38 hours/week (full-time) -- 2.5 years
----- Job description
The Department of Knowledge Engineering (DKE) and the Faculty of Psychology and Neuroscience (FPN) of Maastricht University, the Netherlands, invite applications for a full-time postdoc position with a focus on machine learning and data mining. The position is part of a project funded within the STW/Philips Research Partnership Program on Healthy Lifestyle solutions. The overall goal of the project is to develop a software system that supports overweight people in controlling their eating behavior. The project will be conducted in close cooperation with Philips Research. The successful applicant will have the opportunity to carry out cutting-edge interdisciplinary research in a highly stimulating environment.
PhD in computer science or a related field. Demonstrated expertise in machine learning / data mining. Interest in close cooperation with psychologists. Team orientation and willingness to take a leading role in research. Ability to contribute to teaching at the bachelor and master level. Good programming skills (ideally Java, C++ and iOS) and a background in cognitive psychology are considered a plus.
----- Conditions of employment
Temporary appointment for 30 months. The salary will be set in scale 10 of the collective labor agreement of the Dutch Universities (minimum € 2427,- to €3831,-) for a full-time job (38 hours/week). On top of this, there is an 8% holiday and an 8.3% year-end allowance. Non-Dutch applicants could be eligible for a favorable tax treatment (30% rule). The postdoc will have a workplace at both FPN and DKE.
For further information you can contact Dr. Anne Roefs (FPN, +31 43 3882191, e-mail: a.roefs@...) and Prof. Gerhard Weiss (DKE, gerhard.weiss@...).
----- Application procedure
Interested candidates can apply via the following AcademicTransfer webpage: www.academictransfer.com/21021
The closing date for this vacancy is ***January 12, 2014***
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