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research project “Cities. Building. Culture – The Residential Heritage of the Soviet Union in Times of Multiple Crises” funded by the Federal Ministry of Education and Research (BMBF). This international and
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methods, machine learning algorithms, and prototypical systems controlling complex energy systems like buildings, electricity distribution grids and thermal systems for a sustainable future. These systems
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this interdisciplinary project, we are looking for a strong candidate to contribute to the development of quantum algorithms and applications, focusing on quantum walks and quantum machine learning on graph structures
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integration. Role: Apply ML to barley genomic data, emphasizing gene regulation and genetic variation Collaborate with geneticists, breeders, and industry partners to move research toward applications Explore
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Max Planck Institute for Demographic Research (MPIDR) | Rostock, Mecklenburg Vorpommern | Germany | 3 months ago
links between family and health, [2] the role of genetic factors in shaping health inequalities, [3] international comparisons of health and health inequalities, and [4] developing new methods, in
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research group study the genetic and epigenetic changes that drive the development of hematological malignancies by employing cutting-edge multi-omics approaches. The successful candidate will join a dynamic
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MesaPD to solve complex multiphysics problems. The coupling is done across package boundaries. This also requires more sophisticated approaches in load-balancing. Finally, the newly developed algorithms
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The Network Analysis and Modelling group investigates how genetic variation shapes gene regulation, protein function, and, ultimately, observable plant traits. Using machine learning and network
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sense of touch with low-magnitude normal and shear forces as well as sensing of multiple contact points. Additionally, the end effectors need to be modular to handle different surgical tools. Furthermore
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advanced wet-lab experience in molecular biology and in reverse genetic approaches. • You are familiar with FAIR data handling and in silico data analysis. • You work precisely and reliable. YOU FIT TO US