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oxide (N₂O) emissions by extensive site monitoring testing conservation practices like variable-rate fertilization, and engaging land managers through farm-based tools and a revised European nitrogen
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conditions that enable planners to make informed and responsible trade-offs among conventions and population groups. Tasks: Independent and cooperative qualification through scientific research within
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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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and transfer of science to society. As a modern employer, it offers attractive working conditions to all employees in teaching, research, technology and administration. The goal is to promote and
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, their achievements and productivity to the success of the whole institution. At the Faculty of Computer Science, Institute of Artificial Intelligence, the Chair of Machine Learning for Robotics offers a full-time
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and transfer of science to society. As a modern employer, it offers attractive working conditions to all employees in teaching, research, technology and administration. The goal is to promote and
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for an initial period of 3 years. An extension for up to another 2 years is possible under the above-mentioned condition. The Research Group The advertised position is based in the newly founded Münch Lab (Animal
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chemistry, theoretical chemistry, molecular dynamics, data science, and machine learning are beneficial. What we offer: We offer a position with a competitive salary in one of Germany’s most attractive
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biological catalysts — under operational conditions. Your Responsibilities: Develop and implement in situ EPR methodologies on state-of-the-art spectrometers Conduct research at the intersection
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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