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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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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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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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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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Python and Pytorch as well as deployment on GPU clusters. A strong publication record in graph neural networks, geometric deep learning, representation learning, machine learning–based molecular/materials
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, neural and behavioral data (Allen et al., 2018; Miller et al., 2019; Pedersini et al., 2023). We combine ophthalmological, neuroimaging and behavioral data, and incorporate deep learning methods
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Researcher in FPGA-based AI Hardware Acceleration who has: strong experience in FPGA design, machine learning or a related field in the case of the Postdoctoral Research Associate, a PhD (or near completion
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 13 hours ago
research visits, fostering the dissemination of the findings and collaborations within the academic community. The research topic focuses on fundamental developments of a novel learning framework for
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of Biomedical Informatics (BMI) and the Pelotonia Institute for Immuno-Oncology (PIIO) are seeking a highly motivated Postdoctoral Scholar to work under the mentorship of Dr. Anjun Ma —a leader in deep learning
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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