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to process and understand large experimental datasets (e.g., image processing) #analyzing experimental results; developing conceptual models and parameterizations #scientific publication and presentation
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laboratory (wind-wave facility) experiments, using state-of-the-art imaging techniques developing computational codes to process and understand large experimental datasets (e. g., image processing) analyzing
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enhanced MRI with computer simulations of image contrast and mass spectrometric imaging of tissue samples and single cells. This project is part of the Collaborative Research Centre 1450 “Insight
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and performing laboratory (wind-wave facility) experiments, using state-of-the-art imaging techniques developing computational codes to process and understand large experimental datasets (e. g., image
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the opportunity to contribute to collaborative efforts at the interface of data science, imaging, and materials research. You will strengthen the data science and machine learning activities of the IAS-9 with
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domains are e.g., signal-/image processing, artificial intelligence and machine learning. Tasks: research and development in designing and programming field programmable gate arrays (FPGAs) for accelerating
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learning, or signal processing; familiarity with microscopy data is an asset but not required Interest in foundational machine learning research with applied impact in scientific imaging Demonstrated
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, ideally with knowledge of Drosophila genetics and live imaging the applicant should be able to relocate for 6 months to our collaborator in Chile, where they will develop and optimize novel metabolite
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, ideally with knowledge of Drosophila genetics and live imaging the applicant should be able to relocate for 6 months to our collaborator in Chile, where they will develop and optimize novel metabolite
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that exhibit emergent turbulent behaviors, and (2) disordered optical media that process information through complex light scattering patterns. Using advanced imaging, machine learning techniques, and real-time