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reliability of the AESEC experimental platform. Additional activities, where applicable: Participate in the scientific life of the team and in URANUS project meetings. Occasionally supervise or train PhD
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Post-Doctoral Associate in the Division of Engineering (Mechanical Engineering) - Dr. Mohammed Daqaq
to applicants with expertise in machine learning, wave propagation, metamaterials, and/or fluid–structure interactions. Applicants must hold a Ph.D. in Mechanical Engineering or a closely related discipline, with
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research spans the following broad areas: Complex systems: Nonlinear dynamics and Data assimilation, Statistical physics, Fluid dynamics and turbulence, Condensed matter physics, Biological Physics; Space
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of computational biotechnology and modelling/simulation of bioreactor under aerobic and/or anaerobic treatment of biomass. Candidates should hold a PhD degree with professional experience in biotechnology, process
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, validating models, and publishing high-quality research outputs in peer-reviewed journals About you PhD in an academic field relevant to the discipline. Demonstrated knowledge, confirmed by publications in
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of human biological fluids (such as blood and urine), to ensure successful implementation in various clinical and exposomics applications. In parallel, methods for targeted metabolomics/lipidomics need to be
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). Reactor design (based on CFD modelling), and performance improvements by post-plasma quenching, heat recovery and other downstream processes or combination with catalysts. Computational fluid dynamics
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%) Mentor graduate students in the research group. (5%) Qualifications Required qualifications PhD in Aerospace Engineering Preferred qualifications A strong theoretical/computational background on functional
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, Safety, and Service. Promote equal opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: A PhD degree in Mechanical
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• Interdisciplinary applications ranging from biomechanics and geophysics to fluid and polymer models Further information can be found here: https://www.math.cit.tum.de/math/forschung/gruppen/numerical-analysis