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computing to develop a continuous and local alternative to existing gradient-based learning rules, bridging theories of predictive coding with event-based control/ Simulate models of the learning algorithm
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detectors (Partial) automation of detector characterization for more efficient analysis Algorithm development: Development of a correction method based on information field theory for atmospheric image
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DSP Matlab/C++ Library and of the VPItoolkit DSP Library Implementation of DSP algorithms in MATLAB/C++ Research work in existing projects Research and development in the area of digital signal
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Your Job: As part of an interdisciplinary team, you will develop approaches for the automated and large-scale provision and integration of energy systems data and models and apply data science
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for autonomous systems. Our focus lies on safety-critical applications in the fields of automation, mobility and health. We develop reliable software technologies with a benefit for humans. For example, we conduct
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on these considerations, solutions will be developed and implemented to create an advanced testing platform for the comprehensive evaluation of the long-term stability of invasive brain-computer interfaces. Your task will
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Carl von Ossietzky Universität Oldenburg | Oldenburg Oldenburg, Niedersachsen | Germany | 18 days ago
conservation related consequences of animal navigation, and (4) links biological and technical systems through models, algorithms, and devices. The acquired knowledge can help to solve major societal questions
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serve as a central hub for industry, academia, and policy-making. Together with international research partners, we develop information-theoretically grounded and application-driven algorithms in
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13.01.2020, Wissenschaftliches Personal PhD position at the Chair of Algorithms and Complexity. Candidate shall work on approximation algorithms for scheduling problems in parallel and distributed
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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