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Position: Ph.D. position (all genders welcome)
Institution: Georg-August-Universität Göttingen
Department: Research Training Group RTG 2088
Location: Göttingen, Niedersachsen, Germany
Duties: The Ph.D. candidate will be hosted in the RTG 2088 which focuses on new mathematical concepts for the efficient reconstruction and classification of relevant structural information in data sets, without reconstructing the entire information inherent in the data. One of the guiding principles of this RTG consists of discovering and rigorously exploiting structural a priori information in order to obtain the desired information. Methodologically, specific emphasis will be laid upon the interplay between approaches in statistics, optimization and inverse problems
Requirements: A very good M.Sc. degree (or equivalent) in mathematics or similar fields; A strong background in mathematical statistics and (discrete) geometry; Good knowledge in optimization is beneficial; Good programming skills; Proficiency in written and spoken English
   
Text: Ph.D. position (all genders welcome) Einrichtung: Research Training Group RTG 2088 (ID 100567) Ansprechpartner: Mr. Prof. Dr. Axel Munk, Mr. Prof. Dr. Max Wardetzky Besetzungsdatum: ab sofort Veröffentlichungsdatum: 25.06.2019 The Research Training Group RTG 2088 “Discovering Structure in Complex Data: Statistics meets Optimization and Inverse Problems” at the Georg-August-University Göttingen offers a Ph.D. position (all genders welcome) for the project A5 “Data Analysis with Wasserstein Barycenters” beginning on October 1, 2019. The salary is in accordance with the German public service salary scale (E13 TV-L) with 75% of the regular working hours (currently 29.85 hours per week) for up to three years. In this project at the cutting edge of mathematical statistics (Prof. Dr. Axel Munk) and discrete differential geometry (Prof. Dr. Max Wardetzky) we envision to develop methodology for data analysis based on barycenters which arise from optimal transport metrics. The Ph.D. candidate will be hosted in the RTG 2088 which focuses on new mathematical concepts for the efficient reconstruction and classification of relevant structural information in data sets, without reconstructing the entire information inherent in the data. One of the guiding principles of this RTG consists of discovering and rigorously exploiting structural a priori information in order to obtain the desired information. Methodologically, specific emphasis will be laid upon the interplay between approaches in statistics, optimization and inverse problems. Most of our PhD projects arise from signal applications in biology, medicine or engineering. Candidates have to fulfil the following requirements: - A very good M.Sc. degree (or equivalent) in mathematics or similar fields; - A strong background in mathematical statistics and (discrete) geometry; - Good knowledge in optimization is beneficial: - Proficiency in written and spoken English; - Good programming skills. The University of Göttingen is an equal opportunities employer and places particular emphasis on fostering career opportunities for women. Qualified women are therefore strongly encouraged to apply in fields in which they are underrepresented. The university has committed itself to being a family-friendly institution and supports their employees in balancing work and family life. The mission of the University is to employ a greater number of severely disabled persons. Applications from severely disabled persons with equivalent qualifications will be given preference. Please send your application with the usual documents through our job portal: https://lotus2.gwdg.de/uni/uzdv/perso/knr_100567.nsf . Detailed information on the research topics and training program of the RTG are available at http://www.uni-goettingen.de/de/514290.html . Closing date is August 4, 2019. For further information please contact Prof. Dr. Axel Munk, munk@math.uni-goettingen.de ) or Prof. Dr. Max Wardetzky, wardetzky@math.uni-goettingen.de . Please note: With submission of your application, you accept the processing of your applicant data in terms of data-protection law. Further information on the legal basis and data usage is provided in the Information General Data Protection Regulation (GDPR) Stellensuche Suchen Alle anzeigen Wir weisen darauf hin, dass die Einreichung der Bewerbung eine datenschutzrechtliche Einwilligung in die Verarbeitung Ihrer Bewerberdaten durch uns darstellt. Näheres zur Rechtsgrundlage und Datenverwendung finden Sie im Hinweisblatt zur Datenschutzgrundverordnung (DSGVO) . Kontakt für Anzeigenschaltung Vera Müffeler Postfach 3744 (Gosslerstr. 5 - 7) 37027 Göttingen (37073 Göttingen) Tel. 49 551 39-24213 Fax 49 551 39-1824213 anzeigen@zvw.uni-goettingen.de
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