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2017 PhD Position in Machine Learning at University of Hildesheim, Germany

Applications are invited for a full-time PhD research position at the Information Systems and Machine Learning Lab (ISMLL), Computer Science Department, University of Hildesheim, Germany. The position is available to be filled immediately and offers tenures of three years. The salary amounts to TV-L E13 (roughly 40.000 EUR per year).

The Information Systems and Machine Learning Lab is a research group focusing on machine learning, especially predictive modelling and probabilistic methods. ISMLL takes part in several applied research projects in domains as diverse as e-commerce, technology enhanced learning and traffic management.

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Located in Hildesheim, the University of Hildesheim is renowned for high quality research and education, featuring an International Master Program in Data
Analytics closely related to the research of our group. Hildesheim is a beautiful town with UNESCO World Heritage Sites, located in the very center of
Germany, just 30 km from Hannover.

Qualifications
Applicants should have a recent Master degree in computer science, mathematics or a related area. In particular, any experience in machine learning, data science, data mining, big data, artificial intelligence or statistics will be an asset.

Applicants are expected to have strong analytic and programming skills, the ability to work independently, strong interpersonal as well as English language skills. Upon offer of a position at ISMLL, the candidates who are non-EU citizens are required to obtain an appropriate long-term Schengen visa; further information is available from their nearest German embassy.

Deadline
Applicants are encouraged to apply as soon as possible as the position will remain open until filled by a suitable candidate.

Contact
Please apply online at https://www.ismll.uni-hildesheim.de
Uploading your CV with your transcripts, a research statement, and if available a letter of recommendation from your MSc supervisor or another relevant person. For any question contact Prof. Dr. Lars Schmidt-Thieme via email.

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