Research Associate / PhD Student (f/m/d) - Development of methodologies for high fidelity digit[...]

Overview

The Chair of Structural Analysis is seeking a highly motivated research associate (m/f/d) for a research project focused on developing methodologies for high fidelity digital twin targeting industry-scale wind turbines within the European Horizon Europe MSCA Doctoral Network "Coupled Problems for Decarbonization in Industry and Power Generation" (COMBINE). The position addresses challenges faced by modern wind turbines under changing climate conditions, shifting wind patterns, and structural ageing. The research aims to advance sensitivity-based modelling, fluid–structure interaction (FSI) methods, inverse problem solving, and surrogate modelling techniques, enabling predictive, adaptive, and efficient digital twin frameworks for real-world wind turbines.

Position information

• Application deadline:
• Starting date:
• Position type: full time
• Position duration: 3 years

Responsibilities

• Development of a sensitivity framework for coupled sensitivity analysis.
• Extend the framework to support FSI problems and identify suitable sensitivity computation methods.
• Identify important modelling parameters for the digital model and create a digital wind-turbine model with variable parameters.
• Develop methodologies to solve coupled inverse problems and use measurement/test data to identify high-fidelity modelling parameters by solving the inverse problem.
• Validate the digital model against test scenarios and perform what-if analyses for the developed digital models.
• Develop interfaces to provide feedback from the digital twin to the physical turbine and enhance prediction efficiency with surrogate-model solutions.

Essential Qualifications

• Master’s degree (or equivalent) in Mechanical/Civil/Computational Engineering, or related field.
• Strong background in numerical methods in engineering, computational mechanics, modelling and simulation in CFD/FEA.
• Experience with scientific programming (at least Python and C++).
• Excellent written and spoken English.
• Very strong teamwork skills in international, interdisciplinary settings.
• Very good self-organization.

Desirable Skills

• Very good knowledge of fluid–structure interaction (FSI).
• Experience with digital twins, model updating, or structural dynamics.
• Understanding of optimization, inverse problems, or sensitivity analysis.
• Familiarity with surrogate models (ROMs, ML-based surrogates).
• Motivation for renewable energy and wind turbine technology.

What We Offer

• Fully funded MSCA Doctoral Network position.
• Participation in a cutting-edge research project with high societal importance.
• Vibrant and inspiring research environment within an international multidisciplinary team.
• Working at one of the leading technical universities in Europe.
• Competitive salary and mobility allowance per MSCA rules.
• Joint academic–industrial supervision and mentoring opportunities.
• Access to state-of-the-art data and industrial test cases.
• Structured research and transferable-skills training.
• International secondments with leading European partners.
• Very good preparation for career pathways in academia and industry.

Eligibility (MSCA Rules)

• Eligible for pursuing a PhD at TUM.
• Early-stage researcher (no PhD awarded at the time of recruitment).
• The EU Mobility Rule applies. The candidate must not have resided or carried out their main activity in Germany for more than 12 months in the 3 years immediately before the recruitment date. Compulsory national service, short stays such as holidays, and time spent as part of a procedure for obtaining refugee status under the Geneva Convention are not taken into account.

The position is suitable for disabled persons. Disabled applicants will be given preference in case of generally equivalent suitability, aptitude and professional performance.

How to Apply

Please submit the following to with the subject "Application for COMBINE DC position"

• Curriculum Vitae.
• Motivation letter describing your research interests and specific fit to the offered position.
• Relevant certificates and diplomas, transcript of records.
• Contact details of at least two references.

All the other positions offered by COMBINE can be found at

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