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, together with research experience in at least one class of modern generative models, are particularly encouraged to apply. In addition to conducting research, the successful candidate will teach two courses
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machine learning algorithms to support the traceability of the beef’s geographical origin. She/he will participate in all stages of the project, including planning and supervision of sample collection and
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Learning: Apply shape-correspondence and machine-learning approaches, including spectral/graph-based surface alignment and autoencoder-based shape extraction, to compare limb and joint morphology across
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image analysis packages such as Freesurfer, FSL, SPM, or 3DSlicer, or using machine learning or artificial intelligence models would be advantageous What We Offer The appointee would be exposed to ample
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well as exploring the application of research findings to advanced 3D models such as organoids and 3D bioprinted tissues Learning about high-content, automated phenotypic drug screening pipelines against high
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Researcher position. The selected candidate will work on research and development for testing, analysis, and integration of AI and machine learning (ML) algorithms in new simulation and training architectures
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Specific Requirements The ideal candidate has the following qualifications: - interest in human cognition - experience with neural data, especially EEG or MEG - experience with machine learning models
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of mathematical modeling, with a particular focus on stochastic modeling, optimization and more recently machine learning. Indeed, over the last years, the team’s activity has been marked by a strong shift toward
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analysis, computer vision, or machine learning, with a clear interest in developing image analysis algorithms and an affinity with medical topics. Good communication and organizational skills are essential
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methods You will work closely with: - Dr. Martin Ramacher (machine learning for environmental applications) - Dr. Matthias Karl (urban air quality modelling and emissions) and collaborate within a project