Postdoctoral research fellow HU Berlin

The International Society for Bayesian Analysis; Berlin; On-site; EUR 50,000 - 65,000; Full time

Benefits offered by this job

Opportunities for career development

Collaboration with international networks

Job summary

A leading research institution in Berlin invites applications for a postdoctoral research fellow position in the area of Bayesian deep mixture learning. This role supports the development of high-dimensional statistical models and offers an enriching environment alongside international experts. Candidates should possess a PhD and solid programming experience, ready to contribute to cutting-edge research.

Qualifications

• Completed university degree and PhD required.
• Strong background in Bayesian methods and deep learning preferred.
• Experience in statistical programming and good communication skills needed.

Responsibilities

• Contribute to research in Bayesian deep mixture learning.
• Develop novel methods for deep density regression and clustering models.
• Collaborate with international research teams.

Skills

Bayesian computational methods

Statistical programming

Deep learning

Scientific programming

Communication skills

Education

PhD in Statistics, Mathematics, or related field

Tools

R

Matlab

Python

C/C++

Job description

Postdoctoral research fellow with expected full-time employment E 13 TV-L
HU (third-party funding, limited 18 months)

Postdoctoral research fellow with expected full-time employment E 13 TV-L
HU (third-party funding, limited 18 months) *

* Job description: The working group of Statistics and Data Science at
Humboldt-Universität Berlin invites applications for a position to
contribute to the research on theoretical, mathematical and statistical
aspects of Bayesian deep mixture learning and novel methods towards
high-dimensional deep density regression and clustering models. The research
position can be associated with Prof. Klein’s Emmy Noether group funded by
the German Research foundation (DFG). Opportunities for own scientific
qualification (career development) are provided, see
https://www.wiwi.hu-berlin.de/en/academic-career/academic-career?set_language=en for an overview and further links. The position is to be filled at the
earliest possible date and funded by the Volkswagenstiftung.

* Requirements: Completed university degree and PhD (preferably with very
good marks) in Statistics, Mathematics, or related field with specialisation
in Statistics, Data Science or Mathematics; a strong background in at least
one of the following fields: Bayesian computational methods, mixture models
and inference therein, variational inference, deep learning, density
regression and clustering, model selection priors, mathematical statistics.
Furthermore, a thorough mathematical understanding; substantial experience
in scientific programming with R, Matlab, Python, C/C++ or similar; very
good communication skills and team experience, proficiency of the written
and spoken English language (German is not obligatory) are essential.
We offer the unique environment of young researchers and leading
international experts in the fields. The vibrant international network
includes established collaborations in Singapore and Australia. The position
offer potential to closely work with several applied sciences. Information
about the research profile of the research group and further contact details
can be found through the following link: https://hu.berlin/ENG-StatML .

* Please send your application (including a CV with list of publications, a
motivational statement (at most one page) explaining the applicant’s
interest in the announced position as well as their relevant skills and
experience, copies of degrees/ university transcripts, names and email
addresses of at least two professors that may provide letters of
recommendation directly to the hiring committee) until XX.XX.2020, quoting
the reference number XX/XX/20 to Humboldt-Universität zu Berlin, School of
Business and Economics, Prof. Dr. Nadja Klein, Unter den Linden 6, 10099
Berlin or preferably as a single PDF file to: nadja.klein@hu-berlin . For
further information please contact the project leader Prof. Dr. Nadja Klein
([e-mail])

* HU is seeking to increase the proportion of women in research and
teaching, and specifically encourages qualified female scholars to apply.
Severely disabled applicants with equivalent qualifications will be given
preferential consideration. People with an immigration background are
specifically encouraged to apply. Since we will not return your documents,
please submit copies in the application only.