For any questions, do not hesitate to ask:
Dr. Justin Calabrese Tel.: +49 3581 37523 71
Place of work:
11 April 2023
English / German
Job-Id: 2023/46 (1630)
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.
Bautzner Landstraße 400
PostDoc (f/m/d) in computational modeling of biodiversity in river networks
Through cutting-edge research in the fields of ENERGY, HEALTH and MATTER, Helmholtz-Zentrum Dresden-Rossendorf (HZDR) solves some of the pressing societal and industrial challenges of our time. Join our 1.500 employees from more than 50 nations at one of our six research sites and help us moving research to the next level!
The Center for Advanced Systems Understanding (CASUS) is a German-Polish research center for data-intensive digital systems research. CASUS was founded in 2019 in Görlitz and conducts digital interdisciplinary systems research in various fields such as earth systems research, systems biology and materials research.
To strengthen our diverse team, the Department of Earth System Science at CASUS is looking for a PostDoc (f/m/d) in computational modeling of biodiversity in river networks. The position will be available at the earliest possible date. The employment contract is limited to two years with the possibility of longer-term prospects.
The successful candidate (f/m/d) will be part of an interdisciplinary team studying how river network geometry, hydrology and water quality interact to shape freshwater fish biodiversity patterns in river systems worldwide. In particular, the postdoc will develop and extend dendritic neutral biodiversity simulation models (e.g., Muneepeerakul et al. 2008) in a high-performance computing environment.
- Develop computationally efficient dynamic biodiversity simulation models for river networks (e.g., dendritic neutral models)
- Extend baseline dendritic neutral model to account for variation in water temperature, water quality and deviations from neutral dynamics
- Fit models to fish occurrence and hydrology data from river systems around the world
- Publish results in academic, peer-reviewed journals
- Present results at scientific meetings
- PhD degree in physics, computer science, computational mathematics, computational biology/ecology, computational hydrology, or a related field
- Experience with high-performance computing and shared compute resources
- Advanced programming skills in modern programming languages (Python, C/C++, Julia, R)
- Experience in fitting stochastic simulation models to data
- Experience working with version control systems (e.g., git)
- Excellent communication skills in English in a professional context (presentation of research results at scientific meetings, colloquial discussions, manuscript writing)
- Evidence of the ability to publish results in top peer-reviewed journals
- Knowledge of biodiversity theory is advantageous but not required
- A vibrant research community in an open, diverse and international work environment
- Scientific excellence and extensive professional networking opportunities
- A wide range of qualification opportunities and individual career counseling provided by the Postdoc Center HZDR-TUD
- Salary and social benefits in accordance with the collective agreement for the public sector (TVöD-Bund) 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
Kindly submit your completed application (including cover letter, CV, diplomas/transcripts, etc.) only via our Online-application-system.
Muneepeerakul, R., Bertuzzo, E., Lynch, H.J., Fagan, W.F., Rinaldo, A., Rodriguez-Iturbe, I., 2008. Neutral metacommunity models predict fish diversity patterns in Mississippi–Missouri basin. Nature 453, 220–222. https://doi.org/10.1038/nature06813