Machine learning scientist Jobs in Leipzig

The UFZ

The Helmholtz Centre for Environmental Research (UFZ) with its 1,100 employees has gained an excellent reputation as an international competence centre for environmental sciences. We are part of the largest scientific organisation in Germany, the Helmholtz association. Our mission : Our research seeks to find a balance between social development and the long-term protection of our natural resources.

The job

Are you passionate about cutting-edge research at the intersection of machine learning (ML) and environmental sciences? Do you want to contribute to solving complex challenges in reactive transport modelling using advanced computational techniques? If so, we invite you to apply for a Scientist / PostDoc position in our dynamic research team!

Your tasks

Being part of the OpenWorkFlow project, this position aims to enhance reactive transport modelling by integrating state-of-the-art machine learning methods. Reactive-transport models are critical for understanding and predicting the movement and biogeochemical transformation of contaminants in natural and engineered systems, such as predicting the spread and fate of radionuclides within and around deep geological repositories. However, these models are often computationally expensive and limited by uncertainties in input parameters. This scientist with the possibility of a PhD / PostDoc project will explore how ML may enhance the efficiency, resolution, and predictive power of reactive transport simulations, opening new avenues for environmental and geoscience applications. The candidate will join the department of Environmental Informatics and is tasked, after an intense basic research phase, to finally implement the successfully tested ML techniques into the OpenGeoSys software environment ( This project is under the lead of UFZ but will be conducted together with the Helmholtz-Centre for Geosciences in Potsdam. The successful candidate will work under the supervision of / in close cooperation with Dr. Haibing Shao (UFZ), Dr. Philipp Selzer (UFZ), and Dr. Marco De Lucia(GFZ).

The research work of this position is also linked to the EURAD and DECOVALEX projects, in which inter-code benchmarking and comparisons are conducted on an international level.

Main tasks are :

• Develop and implement novel ML algorithms to improve reactive transport modelling.
• Work with datasets from literature and numerical simulations.
• Collaborate with a multidisciplinary team of environmental- and geoscientists, hydrogeologists, engineers, physicists, and computer scientists.
• Publish your findings in high-impact journals and present at international conferences.

We offer

Your profile