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<p>Doctoral scholarship in machine learning in Frankfurt (Main)</p>
<p>In close co-operation with the German Institute for International Educational Research and Educational Information (DIPF) [1], the Technical University of Darmstadt (TUDA) [2] is offering a doctoral scholarship in machine learning within the newly established
PhD program "Knowledge Discovery in Scientific Publications" [3] on </p>
<p><b>Personalised Content Acquisition from Heterogeneous Sources</b></p>
<p>in the joint Knowledge Mining & Assessment Group at TUDA/DIPF [4] headed by Prof. Dr. Ulf Brefeld. The group focuses on machine learning and information retrieval, such as information extraction and aggregation, recommender systems, and personalisation techniques.
The joint PhD program offers an outstanding opportunity to address numerous highly relevant open questions for future search engines, see [5] for a detailed description of the project.</p>
<p>Excellently qualified graduates in computer science, mathematics, statistics, or related studies are invited to apply. Successful candidates are expected to possess very good mathematical skills, to work independently and to demonstrate their personal commitment,
team and communication skills as well as a readiness to cooperate with others. Solid programming skills (e.g., Python, Java, C/C++) are appreciated.</p>
<p>The program will be located at DIPF in Frankfurt (Main). The scholarship is granted for 36 months for completing a doctoral thesis. Successful candidates will be granted 1,400 Euros per month (tax free). Women are explicitly invited to submit their application.
According to the pursuant legal requirements, applicants with disabilities will be preferably treated in the appointment procedure. Candidates from abroad are encouraged to apply. </p>
<p>The PhD program [3] brings together the disciplines of "Knowledge Engineering", "Algorithmics", "Language Technology", "Ubiquitous Knowledge Processing", "Knowledge Mining and Assessment", and "Information Management". The concept for supervision strongly
relies on close contacts between postgraduate students and their supervisors, regular joint meetings, co-supervision by professors and senior researchers from the above disciplines and a lively exchange in the research and qualification program. </p>
<p>The Department of Computer Science at TU Darmstadt [2] regularly ranks among the top in Germany. Among its distinguishing features are its research initiative "Knowledge Discovery on the Web" focusing on powerful language technology procedures, text mining,
machine learning and scalable infrastructures for assessing and aggregating knowledge. As a scientific institute belonging to the Leibniz Association, the DIPF [1] targets top-class basic research as well as innovative scientific services. Education is addressed
as an area with high visibility and significance. The DIPF is currently establishing a research priority domain for educational information science, by joining competencies with computer scientists at TU Darmstadt. In this context, the doctoral program will
constitute a central element. </p>
<p>Applications should include a letter of motivation related to the research program [3] and the corresponding project [5], CV and details regarding previous scientific work, certifications of studies and work, including the graduate thesis and possibly electronic
publications. Please submit your application in a single PDF file by June 30, 2013. </p>
<p>Applications and inquiries should be sent to Prof. Dr. Iryna Gurevych and Prof. Dr. Marc Rittberger, e-mail: <a href="mailto:phd-application@ukp.informatik.tu-darmstadt.de">phd-application@ukp.informatik.tu-darmstadt.de</a>. </p>
<p>[1] <a href="http://www.dipf.de/">http://www.dipf.de/</a></p>
<p>[2] <a href="http://www.informatik.tu-darmstadt.de/">http://www.informatik.tu-darmstadt.de/</a></p>
<p>[3] <a href="http://www.kdsl.tu-darmstadt.de/">http://www.kdsl.tu-darmstadt.de/</a> </p>
<p>[4] <a href="http://www.kma.informatik.tu-darmstadt.de/">http://www.kma.informatik.tu-darmstadt.de/</a></p>
<p>[5] <a href="http://www.kdsl.tu-darmstadt.de/de/home/research-program/personalized-content-acquisition-from-heterogeneous-sources/">http://www.kdsl.tu-darmstadt.de/de/home/research-program/personalized-content-acquisition-from-heterogeneous-sources/</a></p>
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