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of neural hydrology, where hydrological models are directly learned from data via machine learning (e.g., LSTM neural networks, [1]). Initially, these models ignored all physical background knowledge and did
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solving. Diverse research areas: Work on numerical models, analyzing large data sets, statistical methods and more in a unique scientific environment. Who Should Apply? Emphasizing the physical system
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/NL. The successful candidates commit to actively participate in networking including regular research visits to the partner laboratories. Requirements: university degree in chemistry or physics and
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the latter two being integral parts of the wastewater treatment process. For example, previous studies have shown that a decrease in the number of nitrite-oxidizing bacteria could lead to an accumulation
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Financing yes Type of Position Full PhD Working Language English Required Degree Master Areas of study Physics, Experimental Physics Description Description For our BMBF-funded research project
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presentation and publication of the results Requirements: university degree (Master's or equivalent) in geodesy or a related subject (geophysics, geoinformatics, physics, mathematics) excellent analytical skills
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Successful candidates have strong skills in computational molecular (bio)physics, structural biology and scientific computing, as well as a keen interest in interdisciplinary research and
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research spectrum covers a unique range. Institute of Material and Process Design The Institute of Material and Process Design is dedicated to the sustainable and ecological development of innovative
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. Enhancers, DNA elements with binding sites for transcription factors, play a key role in this process. Recently, it has become clear that enhancer activity requires the formation of sub-micrometer-sized
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(mobile app) intervention for the prevention and management of performance-related pain among musicians. The app will contain various components including self-monitoring, physical exercises, relaxation