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Field
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, hardware-adapted optimization, and error mitigation techniques, aiming to identify requirements, limitations, and pathways for improvement of both hardware and algorithms - analyze variational ansatz
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the necessary algorithms. You will also develop and document a graphical user interface which handles large processing tasks efficiently and uses multiprocessing and GPU acceleration where necessary. At the same
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as well as small-scale EMI measurements with root and shoot observations in controlled experiments (rhizotron facility) and field trials. In addition to field applications, novel inversion algorithms
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required. You will work with the P61A team and our user community to identify the scientific analysis requirements and develop the necessary algorithms. You will also develop and document a graphical user
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that can be used to compare the arrangements • You select suitable algorithms to evaluate the quality of the PPG signals (machine learning, Python) What we offer We offer you a challenging and varied
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physics-aware simulations of growing cell populations, including their spatiotemporal manipulation in microfluidic environments Design and implement reinforcement learning algorithms for control and
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of change Engage in the research, and test the latest machine learning algorithms Analysing, preprocessing, and visualizing different data types (texts, images,etc.) Review latest literature and data
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Neckarsulm, aiming to explore and develop AI algorithms, frameworks, and hardware architectures for efficient edge deployment in vehicles, with a focus on neuromorphic computing. @Fakultät@-Plakat-A4-hoch
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: 28.11.2025 Job description: DESY MorphoSphere develops a powerful data management architecture for a distributed, smart and interactive Storage & Analysis Repository of Digitized Morphology as a pilot project
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in the following research areas: · high-performance data processing on modern hardware · scalable cloud systems · distributed data and storage systems · query optimization and compilation Teaching