2 PhD Positions in Statistics

DFG project "Statistical learning with vine copulas"

12 April 2019
TUM Career - Opportunities for Talents: Symbolbild für Job-Angebote und Stellenaussschreibungen

 

Two PhD positions are available in the research group of Prof. Claudia Czado on vine copula models at the Technical University of Munich.

The focus of these positions is on statistical dependence models using copulas and are supported by the DFG project "Statistical learning with vine copulas". For this model class novel models for quantile regression, clustering and classification are to be developed, implemented and utilized in high dimensional data coming from diverse application fields such as finance, insurance, engineering and/or health sciences. Special emphasis will be given to include discrete data structures.

What are we looking for?

We are looking for candidates with a strong interest in statistical modelling and computational statistics. Programming skills in R or Python are required and C++ would be a plus. Fluency in written and spoken English is a prerequisite.

Applicants for the PhD positions should hold a Master's degree in statistics, mathematics or data science and may obtain a doctoral (PhD) degree in Mathematics.

What do we offer?

The positions have sufficient travel money available to support conference and workshop attendance. The positions are for 3 years. The starting date is 1 October 2019.

The position is paid according to salary grade 75% TV-L E 13 (the standard rate for junior scientific staff at German universities) and can be upgraded to 100% TV-L E13 by adding a teaching load of two contact hours per week. For this upgrade teaching experience and German language skills are required.

As an equal opportunity employer, TUM explicitly encourages applications from women and all others, who would bring additional diversity dimensions to the university.

How to apply

Applications should be submitted by email to cczado (at) ma.tum.de using the subject line "Application". Please enclose transcripts, a CV and the Master's thesis (draft is sufficient).

The deadline is 15 June 2019. We look forward to your application!

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