Research Associate for the Project “AI4PEX” Ocean carbon cycle for contribution to CMIP7 § 28 Subsection 3 HmbHG
Institution: Faculty of Mathematics, Informatics and Natural Sciences, Department of Earth System Sciences
Salary level: EGR. 13 TV-L
Start date: 01.04.2025, fixed until 31.03.2028 (This is a fixed-term contract in accordance with Section 2 of the academic fixed-term labor contract act [Wissenschaftszeitvertragsgesetz, WissZeitVG]).
Application deadline: 2025-02-06
Scope of work: full-time position suitable for part-time
Your responsibilities
Duties include academic services in the project named above. Research associates may also pursue independent research and further academic qualifications.
The project “Artificial Intelligence for enhanced representation of processes and extremes in Earth System Models” (AI4PEX) funded by the European Union’s Horizon Europe research and innovation programme aims to deliver enhanced knowledge on the Earth system by integrating Earth’s Observations (EO), Artificial Intelligence (AI), and Machine Learning (ML) into Earth system modelling and analysis towards more reliable climate projections at global and regional scale. In this sub-project, ocean extremes will be studied using high-resolution observations and high-resolution Earth system model (ESM) simulations. ML methods will be employed to bridge the information from different sources of data and ESM.
The focus of this project at Universität Hamburg will be to investigate the individual and compound ocean extreme events and their precursors based on high-resolution ESM simulations and EO-based fields by leveraging ML methods. Thereby a possible focus can be on the coastal ocean extreme to exploit the power of high-resolution observational datasets. Key factors of large-scale/local-scale conditions in modulating the occurrence of extremes will be identified. The effects of anthropogenic forcings in the presence of internal climate variability on extreme distribution patterns will also be studied to facilitate more reliable future projections.
Successful candidate will be part of a vibrant research group “Modeling the carbon cycle in the Earth system” working in Earth system modeling focusing on the ocean carbon cycle. Responsibilities will include:
- investigating ocean extreme events with high-resolution EO-based observations and ESM simulations
- leveraging ML methods to identify precursors of ocean individual and compound extreme events
- running ESM simulations with the focus on the ocean biogeochemical cycles
- disseminating results through publications in peer-reviewed journals and presentations at conferences
- managing project communication, reporting, and deliverables
Your profile
A university degree in a relevant field, plus doctorate.
- a PhD in oceanography, geoscience, environmental sciences, computer science, or a related field is required for this position
- compelling understanding of ocean biogeochemical dynamics and Earth system modeling
- expertise in statistical analysis and machine learning
- experience in the analysis of extreme events and impacts
- strong programming skills in post-processing, visualization software (e.g., python, CDO), as well as experience in handling large data sets
- strong communication and organizational skills and an ability to effectively communicate results of scientific research to project members and international colleagues
We offer
Universität Hamburg—University of Excellence is one of the strongest research educational institutions in Germany. Our work in research, teaching, educational and knowledge exchange activities is fostering the next generation of responsible global citizens ready to tackle the global challenges facing us. Our guiding principle “Innovating and Cooperating for a Sustainable Future in a digital age” drives collaboration with academic and nonacademic partner institutions in the Hamburg Metropolitan Region and around the world. We would like to invite you to be part of our community to work with us in creating sustainable and digital change for a dynamic and pluralist society.
Severely disabled and disabled applicants with the same status will receive preference over equally qualified non-disabled applicants.
Instructions for applying
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Dr. Hongmei Li |
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Location
Reference number
Application deadline
Use only the online application form to submit your application with the following documents:
- cover letter
- CV
- copies of degree certificate(s)
- names of two professional referees
If you experience technical problems, send an email to bewerbungen@uni-hamburg.de.
More information on data protection in selection procedures.
