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Your Job: Working with a broad range of imaging modalities (e.g. structural, diffusion-weighted and functional MRI, intracranial EEG) Multi-scale modelling of human brain development Using machine
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-driven (machine learning) and model-driven techniques. As part of the DFG research project “Progressive, Spatio-Temporal Consistent Inline Activity Reconstruction and Recognition,” a doctoral position is
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, integrative biology approach that utilizes human pluripotent stem cell based model systems, high throughput functional genomic screening and big data based machine learning, bridging the scales from genetics
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Engineering, or a related discipline. • Strong expertise in machine learning, spiking neural networks, and computer architecture. • Excellent programming and research skills. • Interest in translational
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simulation environments, numerical methods, or machine learning approaches is an advantage Fluent command of written and spoken English is necessary; German is an advantage but not required High degree
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machines into the cellular context in space and time, how stress factors influence these processes, and how the cellular network enables their robust functioning. Research Focus 3 Microbes providing
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Mathematics/ Approximation Theory to be filled by the earliest possible starting date. The Chair of Applied Mathematics, headed by Prof. Marcel Oliver, is part of the Mathematical Institute for Machine Learning
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engineering, software engineering, technical computer scienceor comparable. As robot skills grow in complexity, scalable cloud training becomes essential. Here is the focus on building an AWS-based training
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hosts. The project is centered on the integration and analysis of multiomics datasets utilizing advanced machine learning approaches and biological network analysis. The successful candidate will join an
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advanced machine learning methods for multimodal and 3D medical image analysis in musculoskeletal medicine, in close collaboration with clinicians and computer scientists. PhD or Postdoctoral Researcher