Research Staff in the field of “Scientific Machine Learning”

 

Nestled in a modern city surrounded by nature and with an exceptional standard of living, Leibniz University Hannover offers excellent working conditions in a vibrant scientific community.

The Institute for Steel Construction engages in fundamental and applied research within the framework of doctoral programs, as well as in teaching and academic education in bachelor's and master's programs in civil engineering. The main goal of our research is to improve sustainability in construction towards Net Zero 2050. To achieve this goal, the institute focuses on various research topics such as supporting structures for wind turbines, advanced construction materials, and automated/robotic/additive manufacturing (as one of the key pillars of Industry 4.0 and the next construction revolution).

The Institute for Steel Construction welcomes applications for the following position starting immediately: Research Staff in the field of “Scientific Machine Learning” (salary scale 13 TV-L, 100 %)

The position is initially limited to 24 months, with the possibility of extension. Pursuing a doctoral degree is desired within the context of the advertised position.

Your role

• Your main task is to independently manage advanced research projects in the field of surrogate modelling using physics-informed machine learning (PIML) for efficient scientific simulations. The project focuses on developing efficient predictive models as alternatives to traditional simulation methods like the Finite Element Method (FEM). You will be responsible for researching and applying cutting-edge machine learning techniques to construct models, with a specific emphasis on predicting fatigue lifetime using advanced local methods. Your will also involve validating these models against existing benchmarks, ensuring their reliability in simulating fatigue behaviour. Ultimately, your contribution will help advance predictive modelling efficiency and supporting the development of digital twins for critical structural details.
• Collaborations with national and international research partners, as well as the documentation of research results and their presentation at conferences, and in international journals, are expected.
• Additionally, your responsibilities include actively participating in teaching activities and supervising students in their bachelor's and master's theses.

Who are we looking for?

In addition to a foundational understanding and practical experience of machine learning techniques, you should have a strong ability to independently and quickly familiarise yourself with the new engineering topics. Familiarity with engineering, physics, applied mathematics or similar fields is a strong plus. Additionally, it is advantageous if you already have solid skills in developing and validating numerical models in Ansys or Abaqus and have experience in methodical research as well as the systematic handling of experimental data. Prerequisite for employment is a university science degree (Master) in a relevant field.

In addition, we are looking for a candidate with the following:

• Above-average academic performance
• Advanced skills in programming and numerical analysis (e.g., Python, MATLAB)
• Strong proficiency in machine learning techniques and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)
• Enthusiasm for interdisciplinary research
• Excellent communication skills (spoken and written) in English (C1 level, or equivalents). Knowledge of German is a plus
• Teamwork skills, creativity, and independence

Equal opportunities and diversity are core values at Leibniz University Hannover. Our goal is to tap into individual potential and open up possibilities. We therefore welcome applications from anyone interested in the position, irrespective of gender, nationality, ethnic origin, religion or ideology, disability, age, sexual orientation and identity.

We strive towards a balanced and diverse workforce and a reduction in under-representation in accordance with the Lower Saxony Equal Rights Act (Niedersächsisches Gleichberechtigungsgesetz – NGG). We therefore also welcome applications from women for the above-mentioned position. Preference will be given to equally-qualified candidates with disabilities.

Why join us?

With more than 5.000 employees, Leibniz University Hannover is one of the largest and most attractive employers in the Hannover region. We offer a vibrant interdisciplinary and international working environment, and promote personal and professional development ranging from subject-related skills to leadership and languages.

Part-time employment as well as remote work (mobile work, work from home) can be arranged upon request. We support employees with balancing work and family life, through services such as back-up childcare, childcare during school holidays, and parent-child offices, as well as providing individual advice regarding family responsibilities and caring for dependants.

To promote health and well-being among employees, we offer an extensive sports programme with over 100 different sports, as well as a fitness centre with a sauna and climbing space. Health management measures, such as courses on stress management, good nutrition and relaxation, aim to ensure a healthy workplace.

 

Additional information

For further information, please contact Ms. Dipl.-Ing. Kathrin Löw (email: loew@stahl.uni-hannover.de).

Please submit your application by February 28, 2025 including the usual documents such as a resume and a one-page cover letter for this position, in electronic form (as a PDF file) with the subject: "Stahlbau" to