Doctoral researcher (m/f/d) in Marine Data Science in the project “AI-derived thermodynamic parameters for aqueous modelling (AI-queous)”
Deadline: 19th October 2025
GEOMAR Helmholtz Centre for Ocean Research Kiel is a foundation under public law jointly financed by the Federal Republic of Germany (90%) and the State of Schleswig-Holstein (10%). It is one of the internationally leading institutions in the field of marine research.
Through our research and our commitment to the transfer of knowledge and technology, we contribute significantly to the preservation of the function and protection of the ocean for future generations.
The research unit Marine Mineral Resources of the research division Dynamics of the Ocean Floor – Magmatic and Hydrothermal Systems offers a position for a
Doctoral researcher (m/f/d)
in Marine Data Science in the project “AI-derived thermodynamic parameters for aqueous modelling (AI-queous)”
starting on 01. January 2026 or soon after.
The position offers the opportunity to pursue a doctoral degree in natural or computer science as a member of the graduate school “Helmholtz School for Marine Data Science” (MarDATA). MarDATA is dedicated to training a new generation of “marine data scientists” by integrating expertise from computer science and mathematics into the field of ocean sciences. The school’s interdisciplinary focus spans supercomputing, modeling, (bio)informatics, robotics, statistics, and big data methodologies. Doctoral researchers benefit from a structured training program that promotes cross-disciplinary collaboration and provides in-depth scientific insight as well as a systematic approach to marine data science. For more information, visit: https://www.mardata.de/.
Job Description
As part of the MARDATA doctoral network, the project “AI-derived thermodynamic parameters for aqueous modelling (AI-queous)” invites applications for a PhD position at the intersection of Computer Science and Chemical Oceanography, but with a focus on the Computer Science aspects. The successful candidate will work on the development of a physics-informed, hybrid AI model to calculate key chemical parameters that are currently poorly constrained across an extended range of pressure, temperature, and salinity (pTS). The goal is to improve the predictive accuracy and consistency of such parameters for complex geochemical systems, including deep sea hydrothermal vent environments of geothermal fluids.
This project bridges modern artificial intelligence with geochemical modelling, aiming to deliver transformative advances in the understanding of marine trace elements, resource systems, and subsurface processes relevant to environmental and geoscientific risk assessments.
The work will be conducted within a project consortium led by Dr. Laura Haffert and Prof. Dr. Sylvia Sander (GEOMAR Helmholtz Centre for Ocean Research Kiel), in close collaboration with Prof. Dr. Kevin Köser (Computer Science, Kiel University).
By joining these two groups, you become part of a vibrant and forward-thinking research community at the forefront of ocean science. Sylvia Sander’s group brings geochemistry to life through field campaigns on research vessels, state-of-the-art laboratory analyses, and the development of models that reveal how trace metals behave in various marine environments. Meanwhile, the Marine Data Science Group at the Department of Computer Science (Kiel University) is working on AI technology for ocean observations. Together, these groups are driving innovations that expand our understanding of the ocean and shape how we engage with it in the future.
For further information and applications, please visit: https://www.geomar.de/en/karriere/job-single-en/doktorandin-m-w-d-im-bereich-marine-data-science-im-projekt-ai-derived-thermodynamic-parameters-for-aqueous-modelling-ai-queous