We are looking for the Scientific Computing Center (SCC) for February 1, 2026, limited up to 3 years, for a Scientific Researcher (f/m/d) AI-Based Replacement of Chemistry-Climate Simulations with a Mathematical Focus on Model Understanding and Optimization PhD Position at Faculty of Mathematics 75 % part-time The Scientific Computing Centre (SCC) is a central scientific institution at KIT that performs tasks related to research, teaching, and innovation and provides comprehensive services within KIT and to external parties. This research project focuses on the application of AI models in Earth System Science (efficiently replacement of a chemistry-climate simulation from an Earth System Model (ESM) by an AI-based approach) and the development of mathematically rigorous methodes for interpretable AI modeling and systematic hyperparameter optimization. In detail: Development of a concept to replace the chemistry climate simulation of the ESM with a suitable AI model. This includes testing and selecting appropriate AI architectures (e.g., RNNs, CNNs, PINNs, Transformers), identifying relevant input features, applying dimensionality reduction techniques, and performing hyperparameter tuning (learning rate, number of layers, regularization strength). Training the AI model using a dataset from long-term ESM simulations (from 1979 to 2024), followed by running simulations with the trained AI model. Comparative analysis of AI-based simulations versus traditional ESM simulations, assessing accuracy and performance. Moving beyond a black-box approach, the project aims to achieve a mathematical understanding of the AI model. This understanding should be used to develop systematic methods for optimizing the hyperparameter tuning, grounded in the mathematical areas of optimization theory, statistical learning theory, and explainable AI. The theoretical analysis of this hyperparameter optimization - such as studying convergence properties, regularization effects, and sensitivity analysis - constitutes the core mathematical challenge of the project. This position offers the opportunity to earn a doctoral degree while working in the CSMM research group led by Prof. Dr. Martin Frank and being part of the KIT's KCDS graduate school. Personal qualification Completed studies (master) in mathematics Knowledge of current deep learning frameworks (e.g., PyTorch or Tensorflow) and current AI models Interest in optimization theory, statistical learning theory or explainable AI Ability to work and publish in a targeted and scientific manner Good communication and presentation skills and willingness and ability to work a team Good communication skills in German or English The SCC offers you an exciting and varied job within an agile team as well as a wide range of training opportunities and flexible and family-friendly working time models. We are looking forward to your application including motivation letter, CV and certificates. Become a member of staff of the only German University of Excellence that conducts large-scale research on the national level. Work under excellent working conditions in an international environment and be active in research and academic education for our future. Benefit from specific train-ing when starting your job and from a wide range of further qualification offers. Use our flexi-ble working time models (flexitime, work from home), our sports and leisure offers, as well as our child and holiday care services. We also pay a share of EUR 25/month in the Job Ticket Baden-Württemberg. Enjoy a large variety of dishes, snacks, and beverages at our canteens. We prefer to balance the number of employees (f/m/d). Therefore we kindly ask female applicants to apply for this job. Recognized severely disabled persons will be preferred if they are equally qualified. Please apply online until November 28, 2025 using the vacancy number 447/2025 to Mr Dominik Meschar, Karlsruhe Institute of Technology (KIT), Human Resources, Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany. For further information, please contact Dr. Ole Kirner ( ole.kirner@kit.edu ) and Dr. Jasmin Hörter ( jasmin.hoerter@kit.edu ). For more information about SCC visit: https://www.scc.kit.edu/en/aboutus/working-at-scc.php Processing of your personal data by Karlsruhe Institute of Technology (KIT) will be subject to this Privacy Policy. You can find further information on the internet: www.kit.edu KIT - The Research University in the Helmholtz Association