Research Assistant (Post-Doc) Bergische Universität Wuppertal
Research Assistant (Post-Doc)
The University of Wuppertal is a dynamic and research-oriented campus university. In accordance with its mission statement -Understanding, communicating, shaping-; it faces the social challenges of science, education, culture, economics, society, technology, and the environment. The university is an active member of networks in the region as well as in national and international cooperations. About 24,500 people study, research, or work at 9 schools, research institutions or in university administration.
The School of Mathematics and Natural Sciences, Professorship for Software in Data-intensive Applications, invites applications.
RESPONSIBILITIES AND DUTIES
- Interdisciplinary work at the interface of computer science and mathematics with applications in the context of climate reconstruction within the DFG-funded research project “ICEBAY – Temperature reconstruction combining boreholes thermometry and ice-cores with Bayesian hierarchical modeling.-
- Development and application of probabilistic inference methods and machine learning techniques for quantitative uncertainty modeling and for the integration of heterogeneous climate data
- Collaboration in an international team on related research topics in machine learning, uncertainty quantification, and high-performance computing with applications in the natural and engineering sciences
- Teaching (1 semester hour per week) as well as supervision of term papers and theses
PROFESSIONAL AND PERSONAL REQUIREMENTS
- Completed degree (master or equivalent from university or university of applied sciences) in a relevant discipline (e.g., Computer Science, Mathematics, Physics, Data Science)
- relevant PhD degree
- Strong analytical skills related to statistics, machine learning, and/or (numerical) mathematics
- Excellent command of a programming language (preferably Python or C/C++)
- Interest in modeling and solving a complex, coupled inverse problem in a relevant interdisciplinary application
- Ideally, experience in Bayesian inference or Bayesian hierarchical modeling
- Good command of English (working language within the team, international collaboration)
- A competent, proactive personality with commitment and motivation
- Ability to work independently and enjoyment of teaching
- Successful completion of a scientific programming task in the subject area of the advertised position. All details of the programming task can be found at: https://www.hpc.uni-wuppertal.de/de/peter-zaspel/challenge-in-bayesian-inference-for-climate-reconstruction
This is a qualification position within the meaning of the Academic Fixed-Term Contract Act (Wissenschaftszeitvertragsgesetz – WissZeitVG), which can be filled to promote scientific or artistic qualification. The duration of the employment contract shall be appropriate to the desired academic qualification.
Start
01.10.2026
Duration
up to 3 years
Salary
E 13 TV-L
Time
Full time (Part-time employment is possible, please indicate in your application whether you would also or only be interested in part-time employment.)
Reference Code
26180
Contact person
Mr Prof. Dr. Peter Zaspel
zaspel@uni-wuppertal.de
Applications via
stellenausschreibungen.uni-wuppertal.de
Application deadline
17.08.2026
WE OFFER
Friendly working environment
Flexible working hours and hybrid working
30 days of leave
Family-friendly working conditions
Occupational health management and University Sports
Working in an international context
Large offer of continuing education courses
Company pension scheme
The University of Wuppertal is an equal opportunity employer. Applications from persons of any gender and persons with disabilities as well as persons with an equivalent status are highly welcome. In accordance with the Gender Equality Act of North Rhine-Westphalia, women will be given preferential consideration unless there are compelling reasons in favour of an applicant who is not female. The same applies to applications from disabled persons, who will be given preference in the case of equal suitability.
Applications including all relevant credentials (motivation letter, CV, proof of successful graduation, PhD certificate (if not available yet, provide expected date of finishing the PhD), job references, and if applicable, evidence of a severe disability, ideally Master / PhD thesis – if available) as well as the mandatory completion of a scientific programming task related to the thematic context of the advertised position. All details regarding the programming task can be found at: https://www.hpc.uni-wuppertal.de/de/peter-zaspel/challenge-in-bayesian-inference-for-climate-reconstruction. Kindly note that incomplete applications will not be considered.
Reference number
26180
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