土木与环境工程计算方法博士/博士后

Back to News Board Browse in News Doctoral Researcher and Postdoctoral Researcher Positions in Computational Methods for Civil and Environmental Engineering 05.07.2026, Academic staff Our research combines mathematical modeling, numerical simulation, scientific computing, and data-driven methodologies to improve the predictive capabilities and computational efficiency of large-scale simulations. The Chair of Computational Methods in Civil and Environmental Engineering at the Technical University of Munich (TUM) invites applications for Doctoral Researcher and Postdoctoral Researcher Positions in Computational Methods for Civil and Environmental Engineering in the field of data-driven and model-driven simulation methods for atmospheric flows, ocean and coastal dynamics, and multi-physics systems (eg, wind–structure interaction) . About Us The newly established Chair of Computational Methods in Civil and Environmental Engineering develops advanced computational approaches for challenging problems in environmental and engineering sciences. Our research combines mathematical modeling, numerical simulation, scientific computing, and data-driven methodologies to improve the predictive capabilities and computational efficiency of large-scale simulations. Research Context Climate change is accelerating and increasing the frequency and severity of extreme events such as floods, heatwaves, and severe storms. Advancing clean energy technologies, protecting critical infrastructure, and improving climate prediction models require accurate and efficient simulation tools for atmospheric, oceanic, and coastal processes. Complex environmental systems are characterized by multiple interacting physical processes across a wide range of spatial and temporal scales. The successful candidates will contribute to the development of innovative computational methods that combine physics-based and data-driven approaches to achieve accurate simulations while reducing computational costs. Your Responsibilities Conduct research in computational methods for environmental and engineering applications. Develop and analyze numerical algorithms, reduced-order models, and machine-learning-enhanced simulation techniques. Implement computational methods in scientific software. Collaborate within interdisciplinary research teams. Present research results at international conferences and publish in leading scientific journals. For the PhD position: pursue a doctoral degree at TUM. For the postdoctoral position: contribute to research supervision and proposal development. Your Profile Master's degree (PhD position) or doctoral degree (Postdoctoral position) in Engineering, Mathematics, Physics, Computer Science, or a closely related discipline. Strong background in mathematical modeling, numerical methods, scientific computing, or computational fluid dynamics. Programming experience, preferably in Python, C++, and/or MATLAB. Ability to work both independently and collaboratively. Excellent analytical and problem-solving skills. Good command of written and spoken English. We Offer An exciting interdisciplinary research environment at one of Europe's leading universities. Close interaction with researchers in civil engineering, environmental engineering, applied mathematics, and computational science. Access to state-of-the-art computational infrastructure and high-performance computing resources. Opportunities for scientific networking, professional development, and international collaboration. Salary and benefits according to the collective agreement for the public sector of the German states (TV-L). The positions are suitable for disabled persons. Applicants with disabilities will be given preference in the case of generally equivalent suitability, aptitude, and professional performance. TUM is committed to increasing the proportion of women in research and teaching. Therefore, applications from women are particularly welcome. Application Please submit the following documents as a single PDF file: Curriculum vitae Academic transcripts and degree certificates Brief statement of research interests Contact information for two or three references Applications should be sent by email to: Prof. Annalisa Quaini Chair of Computational Methods in Civil and Environmental Engineering Technical University of Munich E-mail: annalisa.quaini@tum.de Applications will be reviewed on a rolling basis until the positions are filled. Data Protection Information As part of your application for a position at the Technical University of Munich (TUM), you will be transmitting personal data. Please refer to our privacy policy in accordance with Art. 13 General Data Protection Regulation (GDPR) regarding the collection and processing of personal data in the context of your application process: https://portal.mytum.de/kompass/datenschutz/Bewerbung/ By submitting your application, you confirm that you have taken note of TUM's privacy policy. The position is suitable for disabled persons. Disabled applicants will be given preference in case of generally equivalent suitability, aptitude and professional performance. Data Protection Information: When you apply for a position with the Technical University of Munich (TUM), you are submitting personal information. With regard to personal information, please take note of the Datenschutzhinweise gemäß Art. 13 Datenschutz-Grundverordnung (DSGVO) zur Erhebung und Verarbeitung von personenbezogenen Daten im Rahmen Ihrer Bewerbung. (data protection information on collecting and processing personal data contained in your application in accordance with Art. 13 of the General Data Protection Regulation (GDPR)). By submitting your application, you confirm that you have acknowledged the above data protection information of TUM. Kontakt: annalisa.quaini@tum.de Print

Master's degree (PhD position) or doctoral degree (Postdoctoral position) in Engineering, Mathematics, Physics, Computer Science, or a closely related discipline. Strong background in mathematical modeling, numerical methods, scientific computing, or computational fluid dynamics. Programming experience, preferably in Python, C++, and/or MATLAB. Ability to work both independently and collaboratively. Excellent analytical and problem-solving skills. Good command of written and spoken English.