Postdoctoral Researcher (f/m/d) in Machine Learning and Surrogate Modeling for Geochemical Systems - 2026/32
Postdoctoral Researcher (f/m/d) in Machine Learning and Surrogate Modeling for Geochemical Systems - 2026/32
Postdoctoral Researcher (f/m/d) in Machine Learning and Surrogate Modeling for Geochemical Systems - 2026/32
Postdoctoral Researcher (f/m/d) in Machine Learning and Surrogate Modeling for Geochemical Systems - 2026/32
Helmholtz-Zentrum Dresden-Rossendorf (HZDR)
Sonstige Branchen
Görlitz
- Art der Beschäftigung: Teilzeit
- 53.500 € – 71.000 € (von XING geschätzt)
- Vor Ort
- Zu den Ersten gehören
Postdoctoral Researcher (f/m/d) in Machine Learning and Surrogate Modeling for Geochemical Systems - 2026/32
Über diesen Job
Dr. Attila Cangi Tel.: +49 3581 37523 52
Job-Id: 2026/32 (2205)
At HZDR, we promote and value diversity among our employees. We welcome applications from people with diverse backgrounds regardless of gender, ethnic and social origin, belief, disability, age, and sexual orientation. Severely disabled persons are given preference in the event of equal suitability.
Helmholtz-Zentrum
Postdoctoral Researcher (f/m/d) in Machine Learning and Surrogate Modeling for Geochemical Systems
With cutting-edge research in the fields of ENERGY, HEALTH and MATTER, around 1,500 employees from more than 70 nations at Helmholtz-Zentrum Dresden-Rossendorf (HZDR) are committed to mastering the great challenges facing society today.
The Center for Advanced Systems Understanding (CASUS) is a German-Polish research center for data-intensive digital systems research.
CASUS is looking for a Postdoctoral Researcher (f/m/d) in Machine Learning and Surrogate Modeling for Geochemical Systems.
Your tasks
- Identify existing machine learning approaches applicable for geochemical systems in a geological setting
- Implement, adapt, and apply machine learning approaches and mathematical surrogate models for modeling radionuclide migration in crystalline host rocks
- Perform uncertainty quantification of machine learning and surrogate models with respect to traceability, robustness and physicochemical correctness
- Cooperate with our project partners at HZDR, TU BA Freiberg and TU Darmstadt
- Present your scientific findings at academic venues and publish research in peer-reviewed journals
Your profile
- Ph.D. in the field of Physics, Chemistry, Computer Sciences or Applied Mathematics or related field
- Background in mathematical surrogate modeling and machine learning
- Experience or familiarity with large-scale computational simulations
- Prior exposure to collaborative software development and version control systems (Git)
- Motivation to work collaboratively in a team-oriented environment
- Proficiency in programming languages (Python, Julia, C/C++)
- Excellent communication skills in English
Our offer
- A vibrant research community in an open, diverse and international work environment
- Scientific excellence and extensive professional networking opportunities
- Salary and social benefits in accordance with the collective agreement for the public sector ( TVöD-B und) including 30 days of paid holiday leave, company pension scheme (VBL)
- We support a good work-life balance with the possibility of part-time employment, mobile working and flexible working hours
- Numerous company health management offerings
- Employee discounts with well-known providers via the platform Corporate Benefits
- An employer subsidy for the "Deutschland-Ticket Jobticket"
We look forward to receiving your application documents (including cover letter, CV, diplomas/transcripts, etc.), which you can submit via our online-application-system.
