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Neurodegenerative Erkrankungen e.V. (DZNE) a W2 professorship for Multimodal Sensor and Analytics Systems in Dementia Research with the framework of a joint appointment according to the Jülich model. The Rostock
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-body positron emission tomography (PET) with magnetic resonance imaging (MRI). In conjunction with the development of algorithms, dedicated software and hardware-based simulations will be developed
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of the following topics: physical layer design for ultra energy-efficient wireless spike-based sensor node communication digital baseband design for energy-efficient terabit/sec wireless communications using
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(with an option to extend the contract by a further 3 years). The medical physics group is working in the field of biomedical photoacoustic imaging and sensor technology. We are developing novel
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their glial niche. Genetically encoded, fluorescent metabolite sensors will be used to study the underlying metabolite dynamics. The work will also incorporate various molecular biology techniques, as
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spectroscopy. The present project will involve the following steps: • Development of scanning probe near-field sensors based on solution-synthesized metallic nanoparticles • Operation of an existing setup
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qualification (usually PhD). Tasks: The aim of the project is to design, model, fabricate and test a wireless micro-sensor which uses magnetic fields for sensing in biological soft tissues. For further
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University professorship (m/f/d) in 'AI in Occupational, Social and Preventive Medicine' (salary gra
implementation of AI algorithms and tools for analyzing and predicting health-related events, process optimization and decision support in healthcare. Validation of models to ensure accuracy and reliability
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learning algorithms (e.g., graph neural network (GNN) architectures) will be developed to explain the identified small-scale processes as accurately and efficiently as possible and to ultimately develop a
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and analysis of mathematical methods for novel imaging techniques and foundations of machine learning. Within the project COMFORT (funded by BMFTR) we aim to develop new algorithms for the training