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Field
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opportunities offered by cutting-edge CFD methods. Prior experience in CFD and/or CFD code development (e.g., Python, Fortran, C++) would be a considered as a strong asset. Selection process The recruitment
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with programming languages such as Python, MATLAB, or similar, and are interested in combining analytical modelling with data-driven or AI-based approaches. You are self-driven, curious, and able to work
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/Qualifications Profile - A solid background in continuum mechanics and computational mechanics is required. Advanced knowledge in scientific programming is also requested (e.g. Python, Matlab, possibly FORTRAN
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, Computational Biophysics, or a closely related field Strong programming skills (e.g., Python, C/C++) Knowledge of machine learning frameworks (e.g., PyTorch, TensorFlow) Very good English language skills, ability
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of the introductory mathematics and statistics courses. Familiarity with computer programming, e.g., Python, Julia, R, etc. Personal characteristics Motivation for conducting research at an advanced level. Ability
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discipline prior to enrolment. The successful candidate should demonstrate: Strong programming skills (e.g. Python, C++ or similar) Solid foundation in linear algebra, geometry, and optimisation Experience
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. Objectives: Using our in-house python-based nonlinear aero-thermo-structural finite element solver you will investigate, understand, and optimise the behaviour of flight structures subjected to relatively
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semiconductors. You should have experience working in a laboratory environment, along with basic programming and data analysis skills (Python, MATLAB, LabVIEW). High motivation, very good English or German skills
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programming, preferably Python and R, is required. Experience with mass spectrometry data, in particular metabolomics, and geometric machine learning is a plus. In addition to above-average interest in
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biochemical models, data assimilation, spatial analysis and GIS approaches. • Programing skills (e.g. R or Python) for data manipulation and visualisation, and to perform statistical analysis (e.g. mixed models