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– from the modeling of material behavior to the development of the material to the finished component. PhD Position in Machine Learning and Computer Simulation Reference code: 50145735_2 – 2025/WD 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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computational scheme which allows efficient and accurate computer simulations of biofabrication. Using this novel tool in collaboration with our experimental colleagues we will thrive to understand the physical
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uncertainty characterisations for mass balance estimates from satellite altimetry applying the results in comparative studies and combination studies with complementary methods such as satellite gravimetry
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Description Wastewater treatment plants (WWTPs) are estimated to contribute 8 – 11% of the methane and 2.7% of the nitrous oxide global gas emissions. Methane and nitrous oxide are greenhouse gases
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, as well as methods of parameter estimation and stochastic modelling experience in analysing processes interlinking solid Earth and ice sheet would be an asset excellent problem-solving skills and
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of computer simulations to refine the targeted synthesis even more and predict the self-assembly even better. Who we are The Research Training Group RTG2670 – Beyond Amphiphilicity in the second funding phase
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., Diploma) in either computer engineering, computer science, electrical engineering or any related natural science very good programming skills in C, C++ fluency in English, knowledge of German would be a
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parametrization, estimate N-mineralization rates from soil organic matter content and other N-balance components support monitoring, reporting and verification of greenhouse gas emissions and mitigation efforts