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messengers transported by the flow or even the pressure of the fluid itself. In an interdisciplinary team, you will either develop theoretical models of the feedback between flow and network architecture
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for the modeling and simulation of 3D reconfigurable architectures e.g. based on emerging technologies (e.g. RFETs, memristive devices), and the evaluation with e.g. machine learning and image processing benchmarks
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data. You bring first experience with biostatistics methods, e.g. with mixed-models. You are familiar with data analysis using programming languages like R, and/or Python. You have excellent
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organized manner and pay attention to details. ▪ You thrive on finding solutions to complex problems. ▪ You have strong communication and writing skills. What can you expect in return: ▪ A curiosity-driven
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networks involved in CHC perception, particularly in the context of prezygotic reproductive isolation within a species complex of parasitoid wasps (Nasonia). Our previous research has already deciphered
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of molecular and biological materials using X-ray and neutron scattering. The main research areas are materials for photovoltaics, proteins in solutions and at the interfaces, and complex nano-structured
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using X-ray and neutron scattering. The main research areas are materials for photovoltaics, proteins in solutions and at the interfaces, and complex nano-structured materials. For more information, visit
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geoinformatics in addition to scientific computing. By using the tools of informatics in this subject, anyone can study or model objects, structures, regulatory networks, or processes (signals, materials and
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of human-environment research. The general theme associates process mapping and modelling, creation of material balances (water, air, sediment, carbon, nitrogen and pollutants), the reconstruction of past
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of mathematical models to the development of new imaging-related techniques and compounds. The programme is searching for excellent students who hold a Master's degree in Biology (or related fields), Physics