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Details Posted: Unknown Location: Salary: Summary: Summary here. Details Posted: 16-Aug-25 Location: New York, New York Categories: Academic/Faculty Internal Number: 172205 Postdoctoral Researcher
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About the Role The combination of personalised biophysical models and deep learning techniques with a digital twin approach has the potential to generate new treatments for cardiac diseases. Our
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dimensional information, classification and/or deep learning methods may also be developed. In addition, the complementarity between the different data sources used (particularly between aerial LiDAR data and
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Internal Number: 6513057 Postdoctoral Scholar - Fermentation Science - California Institute for Quantitative Biosciences (QB3 Berkeley) Position overview Position title: Postdoc Employee Salary range: The UC
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SD-25157 RESEARCHER IN ATMOSPHERIC PLASMA TREATMENT OF METALLIC SURFACES FOR INDUSTRIAL APPLICATIONS
will support the implementation of robust, efficient surface modification solutions in industrial settings. The postdoctoral researcher will conduct research in the atmospheric plasma treatment
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Internal Number: 6550655 Postdoctoral Scholar - Process Simulation and Techno-Economic Analysis - California Institute for Quantitative Biosciences (QB3 Berkeley) Position overview Position title: Postdoc
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? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Postdoctoral position in Development and application of computational methods
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outcomes ●casual representation learning for real-world data ● deep learning interpretation, fairness and robustness ●Regularly conduct computational experiments to execute algorithms on various health and
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, including use of scientific libraries (e.g., NumPy, SciPy, scikit-image, PyTorch/TensorFlow). Experience with deep learning or machine learning approaches to image denoising and reconstruction. Prior exposure
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related discipline. The candidates will have expertise in computational imaging, with: (i) an algorithmic focus, with particular interest in methods at the interface of deep learning and optimisation