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(Methods for Active Informed Machine Learning). This project is a close collaboration with the Hasso Plattner Institute. We are developing and improving machine learning methods by integrating domain
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hours per week), based in Berlin. Your Tasks Development of software for the analysis, management, and interpretation of omics data Selection and benchmarking of algorithms, libraries, and tools
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will work in a group with other students and take on specific tasks. The aim is to analyse the robot's capabilities and to implement algorithms that enable the robot to be used sensibly in applications
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structure, efficiently solving problems in HOBO ("higher order binary optimization") formulations, or exploring Grover-inspired algorithms and Quantum Imaginary Time Evolution. What you bring to the table
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Your Job: This thesis focuses on designing, evaluating, and deploying algorithms for robot perception and control. The main task is predicting both self-motion and the motion of surrounding agents
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multi-parameter ion-beam tuning procedures (collaboration with Univ. of Vienna and HZDR) and developments of machine learning (ML)-algorithms for optimization of beam parameters and control of relevant
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The »High-Performance Cutting « department develops technologies and application-oriented solutions for machining along the entire process chain - from process design and process simulation to real
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, execution and analysis of three cooperative sub-projects within the FADOS network: The development of kinetic Monte-Carlo algorithms with realistic working parameters which account for inhomogeneous and
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of terrestrial systems analysis, we seek a candidate who can develop and lead future research activities in one or more of the following directions or related topics: Innovative observation methods for terrestrial
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and digitization. More than 400 employees – including around 100 students – from over 50 countries work at nine locations in scientific and non-scientific teams on the development of innovative methods