821/2022 Environmental Data Scientist (f/m/d)
KIT-Campus Alpin (IMK-IFU) operates a broad spectrum of observation systems and models. These range from classical climate stations to modern remote sensing systems and greenhouse gas sensors to extensive numerical model systems. In such a diverse data landscape, modern machine learning approaches in particular have the potential to provide new insights into our climate system and interactions between different climate-related processes through the multivariate intersection and consideration of the different data sources.
Your task is to establish and actively develop a FAIR data infrastructure for the diverse data of the institute. Furthermore, you will develop Data Mining and Machine Learning approaches for the identification and application of spatio-temporal correlations of climate-relevant variables in close coordination with our scientists. Special emphasis is put on the use of international standards for (meta)data, the provision via standardized interfaces as well as the use and further development of community tools for the exploration and analysis of environmental science data.
The position is embedded in the working group IFU DataInitiative & DataManagement. Within this framework, you will form a central interface between the scientists of the institute and coordinate and support the various activities in the field of Data Science / Machine Learning both at the institute and in higher-level groupings at national and international level.
Your responsibilities will include:
- Development of data pipeline architectures from sensor to analysis-ready-data
- Implementation of quality checks (Qa/Qc) for various data sources
- Development and application of Big Data analytics solutions in the areas of Environmental Data Science / Machine Learning and Data Mining, including own publishing and acquisition of projects
- Data science as-a-service: coordination, support and development of workflows of scientific work in the areas of Machine Learning, QA/QC.
- Master and / or PhD in (Geo-)Informatics, Computer-, Geo- or Environmental Sciences, Mathematics, Physics or a related STEM subject with strong relation to Scientific Computing and Programming.
- Very good programming skills in Python (esp. PyData ecosystem) and several years of experience in (Environmental) Data Science / Machine Learning.
- Documented experience in the use / analysis of climate and environmental science data
- Experience in using cloud computing infrastructures (Kubernetes, Object Storage, etc.), container solutions (Docker, Singularity), modern software infrastructure (Git, CI/CD, etc.) and data pipeline development and quality assurance is a plus
- Fluent in written and spoken English, fluent in written and spoken German is an advantage
- Very good oral and written communication and coordination skills and motivation to work in an interdisciplinary environmental research team.
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W3-Professorship for Impact-Based Forecasting
In Division IV - Natural and Built Environment - within the KIT-Faculty of Civil Engineering, Earth and Environmental Sciences, a university professorship (W3) "Impact-Based Forecasting" is to be filled at the earliest possible date. The university professorship (W3) will perform large-scale research tasks in frame of the Helmhotz programme activites, has thus a reduced teaching obligation of 2 hours weekly, and will be head of a new department at the Institute of Meteorology and Climate Research (IMK).
This Real-World-Lab Professorship is a core element of the new Real-World-Lab "Real-Time decisions in the event of risky ignorance in the impact prediction of extreme events (ERNIE)" to be established in 2023/24. It forms a tandem with the – in parallel - advertised W3 professorship "Decision making under high risk and high uncertainty" in Division II - Informatics, Economics, and Society - within the KIT Faculty of Humanities and Social Sciences.
This professorship tandem is established to conduct research and teach both disciplinarily and inter- and transdisciplinary, in particular also on the question of how transformative processes can increase the resilience of society towards extreme events. KIT will thus expand its leading role in Real-World-Lab research.
We are looking for a recognized personality (f/m/d) in the field of risk research with excellent academic qualifications in their field. The thematic focus of the professorship is on the development and application of integrative impact and prediction models for different high-impact events in the field of climate and environment (storms, heavy precipitation/floods, convection, heat waves). The basis for this are your excellent scientific achievements, proven by relevant publications and projects.
In teaching, you represent your field of expertise in a didactically competent matter in basic and in-depth courses. Research-oriented teaching - one of the fundamental principles at KIT - complements disciplinary teaching and brings in real-lab research into the respective curricula. In addition, you bring in your expertise and experience to the training of young scientists.
Participation in academic self-administration is just as much a part of the KIT faculty's self-image as interdisciplinary cooperation and the acquisition of third-party funds for research and innovation. A habilitation or equivalent qualification, which may also have been acquired outside the university, as well as proven didactic skills and teaching experience are required.
Employment conditions as outlined in Article 14, par. 2 of the KIT Act in conjunction with Article 47 of the Act of Baden-Württemberg on Universities and Colleges (Landeshochschulgesetz Baden-Württemberg) apply.
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