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Field
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on developing algorithms and foundations for deep learning and foundation models, particularly for medical imaging and on establishing mathematical and empirical underpinnings for machine learning. We
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are working with a PhD student and a research fellow who have collected underwater data and preliminary algorithms. With their guidance and supervision, project aims and objectives are expected to be achieved
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to cutting-edge tools, algorithms, and large, high-quality seismic datasets. Occasional fieldwork to acquire data from temporary networks, providing you with hands-on experience in the field. A competitive
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, algorithm design, optimisation and simulation, software engineering and automation and control systems. An overview of the current PhD research projects is given here: https://www.dashh.org/research
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, their achievements and productivity to the success of the whole institution. At the Cluster of Excellence „Physics of Life” (PoL), the Heisenberg Chair of Biological Algorithms (Prof. Dr. Benjamin Friedrich) offers a
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for space logistics. With the development of mathematical models and optimisation algorithms, we aim to support strategical, tactical and operational decisions in the context of the deployment of in-orbit
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relevant background in algorithms and/or database systems with a research-oriented master’s thesis. Good programming skills. Good written and oral English language skills. Your education must correspond to a
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the development of new algorithms for processing, analysis and inversion of active and passive seismic data and the application of these algorithms to field data. Student type Future Students Faculties and centres
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education . Skills and personal qualities In addition to the aforementioned requirements for the position: A demonstrable computational competence, comfortable with using and developing algorithms, data
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the autumn of 2025 or as agreed. Project description This doctoral position has a special focus on sustainable data cultures, algorithmic decision-making and AI solutions within municipal companies