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integration of methodological development and practical applications. We maintain extensive collaborations with industrial partners as well as with leading research groups worldwide, providing doctoral students
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simulation of time dependent non-linear PDEs has emerged as a key technology. A main task of this employment is the development and analysis of numerical methods for wave propagation problems. Particular focus
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modelling, data assimilation, and multi-scale neural network architectures applied to spatio-temporal data. The development of these methods is motivated by a concrete and important application: inferring gas
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functional studies using intestinal organoids, combined with analysis of viral evolution during course of infection, will be performed to understand mechanisms behind infection susceptibility, virus
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look forward to receiving your application! Do you have a background in machine learning and interested in telecommunications? You have a chance to contribute to development of sensing methods for new
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characterized by close integration of methodological development and practical applications. We maintain extensive collaborations with industrial partners as well as with leading research groups worldwide
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spectrometry, thermal analysis, mechanical testing) Your PhD research will contribute to the development of next-generation bio-based materials from forest resources. Within the GreenPolChem group and WWSC
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We are seeking a PhD candidate to join our team in the development of next-generation bioelectronic platforms to study implant interfaces and modulation of the brain tissue microenvironment
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contribute to the development of next-generation bio-based materials from forest resources. Within the GreenPolChem group and WWSC, this work will be performed in a highly interdisciplinary research
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application! Your work assignments We are looking for a PhD student to work on the development of novel spatio-temporal machine learning methods. Our world is inherently spatio-temporal, i.e. physical processes