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breakage models, e.g. with stochastic tessellations Development and implementation of estimation methods for the model parameters, e.g. with machine learning or statistical methods Lab work and collection
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, remanufacturing, repurposing and recycling to each other for the realization of an agile network. Various machine learning approaches will be used here. Your tasks are: Requirements definition, survey and
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Framework for Its Further Monitoring. Sustainability , 12 (14), Article 14. https://doi.org/10.3390/su12145682 Carretta, L., Cardinali, A., Masin, R., Zanin, G., & Cederlund, H. (2020). Decyl glucoside
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are a small international team based at the Max Planck Institute for Multidisciplinary Sciences in Göttingen, Germany. We aim to understand how molecular machines select transmembrane cargo proteins and
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quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation and the ability to work independently with a strong team orientation excellent spoken and written English and the
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. - Neural networks and machine learning strategies for the analysis of scattering data. Large amount of scattering data obtained in our group requires development of the advanced analysis techniques. In
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plant genetic mechanisms that coordinate mycorrhizal interactions with plant P and water status, root system development, and soil microbial communities. Using maize and rice as models, we will: 1
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challenging, and new theoretical methods and algorithms are required. The research project aims at deriving priors for Bayesian methods from atomistic simulations and machine learning. It also offers
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and the conditions under which desorption may occur. Little is known about how environmental ageing and transport affect the sorption behavior of plastic particles. In arable soils, key knowledge gaps
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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