Conduct innovative research in the field of data science and its applications specifically in the area of climate change research., Substantially contribute to the methodological development in data-driven analysis., Demonstrate that newly developed techniques have brought already substantial new insights in their field of application., Advancement of machine learning- /artificial intelligence-methods for application in Earth systems science and modelling, Methodological development, e.g. in the context of Deep Learning for data-driven modelling of climate phenomena, Machine learning for Earth system modelling and downscaling, Physics-informed machine learning to combine physical and machine-learning approaches (hybrid modelling), Advancement of non-linear and complex systems theory in the context of climate applications, Application and development of advanced data analysis methods in the field of climate change research, Advancement of interdisciplinary approaches., Teaching obligations amount to two hours per semester-week in the field of Climate Change & Data Science for Complex Systems at the TU Berlin., Leading and managing the department and its staff, Supporting the advancement of junior scholars, women, and diversity, Knowledge and/or technology transfer, Initiatives to promote internationalization, Gender and diversity competence, sustainability-oriented action as well as committee work.