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Field
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learning algorithms (e.g., graph neural network (GNN) architectures) will be developed to explain the identified small-scale processes as accurately and efficiently as possible and to ultimately develop a
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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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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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that process planning has a high potential for automated optimization. Building upon this, you will advance our optimization pipeline and evaluate different optimization algorithms/strategies. What you will do
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Fraunhofer Institute for Wind Energy Systems IWES | Bremerhaven, Bremen | Germany | about 1 month ago
diverse working day is guaranteed! During the project, you will develop and implement self-learning control algorithms that balance computational demand and modeling precision. You will evaluate, interpret
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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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of software interfaces and data models Selection and configuration of algorithms for annotating and organizing research data and software using state-of-the-art AI technologies Ensuring the sustainability and
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diverse working day is guaranteed! During the project, you will develop and implement self-learning control algorithms that balance computational demand and modeling precision. You will evaluate, interpret
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group focuses on developing strategies and algorithms to quantity biologic effects of particle radiation based on underlying physics, biology and physiology. Within the BMFTR funded project “BIOMICRO
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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