10 PhD program in « High Dimensional Non Stationary Time Series »
The International Research Training Group (IRTG) 1792 ´High Dimensional Non Stationary Time Series´ is a flagship program with extensive funding supported by DFG, linking two top universities and two outstanding faculties. IRTG 1792 offers outstanding young researchers a full-time, internationally competitive PhD program with a unifying research focus and financial support in the form of scholarships.
The IRTG´s doctoral framework is based on the unifying research theme ´High Dimensional Non Stationary Time Series´, and its focus is on identifying low dimensional factors that help to forecast and understand dynamic aspects of possibly non stationary economic data in high dimension. It combines demanding course work and a particularly early start of individual research in the following areas of high dimensionality, non-stationary, time varying dependency and others.
With its participating faculty, the IRTG represents all major academic institutions of statistics and economics in Berlin and Xiamen: Humboldt- Universität zu Berlin, Xiamen University, Freie Universität Berlin, WIAS, and DIW.
Application period: January 1. up to March 31.
Language of the Doctoral Thesis
Requirements for Applicant
Subject Requirements (Qualification)
We are looking for highly qualified and highly motivated PhD students with an M.A. or equivalent degree. The applicants should have a quantitative background, preferably in statistics, economics, mathematics or other related fields. A good knowledge of English is also required.
For more information on requirements and how to apply please refer to:
Type of Persons
- Curriculum vitae
- Copy of university degree
- High school diploma
- Letter of motivation
- 2 academic references
- GRE scores
- TOEFL or IELTS scores
University / Organisation advertising the position
University / Organisation
Faculty / Institute
Center for Applied Statistics and Economics (C.A.S.E) of Humboldt- Universität zu Berlin and Wang Yanan Institute for Studies in Economics (WISE) of Xiamen University
Coordinator / Supervisor of the Doctoral Thesis