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assays and drive the development and implementation of new technologies. develop new bioinformatic workflows and pipelines. work together with an interdisciplinary team of bioinformaticians, biologists and
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Isaac Sim, ensuring realistic physics for hybrid locomotion. You will develop and train RL algorithms for hybrid locomotion tasks, including transitioning between locomotion modes and balancing on uneven
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research. You will strengthen the data science and machine learning activities of IAS-9 by developing core AI methods with applications to electron microscopy and materials discovery. You will work in a team
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: Development of machine learning algorithms for the localisation of seismic sources (e.g., on 2D grid maps) Analysis and preprocessing of large DAS datasets Use of synthetic training data from seismic
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can therefore draw on the expertise of a strong network. At Fraunhofer Institute for Industrial Mathematics ITWM, we see our task as further developing key technologies, providing innovative impetus
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, the objective of this thesis is to develop and test a real-time, tightly-coupled traversability algorithm that fuses information from both sensor modalities, therefore providing a more complete understanding of
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effectively over extended distances. For this purpose, it is essential to develop a robust mapping algorithm, that allows for continuous, online map growth during exploration and mapping operations. The map
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(e.g. RNAi, CRISPR/Cas9, small-molecules). In this context, we also develop new computational tools for automated analysis and data visualization. These include algorithms and software applications
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Future. Discover. Together. The Wireless Communications and Networks department at the Fraunhofer Heinrich Hertz Institute develops new technologies for the next generation of wireless communication
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algorithms for microscopy image analysis problems (primarily 2D timelapse data), which are driven by real applications in life science research Develop solutions to integrate large foundation models