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as of the 01.04.2026 at the following conditions: 50% = 19,92 hours Pay grade 13 TV-L limited by 31.03.2029 Your tasks: Development of architectures and algorithms for adaptation of time-triggered
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Doctoral student in development of nanowire devices for photonic neuromorphic computing (PA2026/472)
and analytically, to solve problems independently using the right methods, and to develop an awareness of research ethics. In addition, you will have the opportunity to work on projects, to develop your
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machine learning methodologies, develop algorithms for health monitoring and patient clinical outcome prediction, and address ethical considerations. The role also requires attending weekly meetings, report
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the development of mathematical models for signal transmission and reception, derivation of fundamental performance limits, algorithmic-level system design, and performance evaluation through computer simulations
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development of post-graduate students. Particular attention will be given to candidates with experience in topics that are relevant to data science, most notably mathematical and algorithmic foundation
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the development, evaluation and application of innovative AI, machine learning and systems approaches to modeling biomedical big data for precision health. We are particularly interested in AI methods
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, such as new topological states, magnetism, electrical/thermal transport, superconductivity, and corresponding material predictions. (2) Develop numerical algorithms and computing software, such as
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environment to support agricultural decision making with advanced remote sensing and geospatial technologies. Responsibilities: Develops advanced Agro-geoinformatic algorithms for monitoring and predicting
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complex biological systems. Research Environment & Collaboration The successful candidate will work at the interface of machine learning and biostatistics, developing new theory, algorithms, and scalable
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Projection Chambers used in the Deep Underground Neutrino Experiment. This work involves parsing the simulated data to extract and analyze the information necessary to develop an algorithm to determine the