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Field
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(CHX, 11-ID) beamline at NSLS-II seeks a postdoctoral researcher with a strong background in computational imaging, data science, or scientific computing. This position will focus on developing advanced
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You will develop and validate advanced AI models that integrate medical imaging, multi-modal clinical and omics data, and explainable AI (XAI) for the prediction of hepatocellular carcinoma (HCC
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BioNanoImaging Foundry (BNIF, Building 50, Triolet campus). The BNIF is a cutting-edge technological environment dedicated to multimodal imaging, equipped with high-field MRI scanners (9.4 T, 3 T horizontal
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(currently at Southampton University) and with data processing experts in the MATISSE international consortium. Her/His first main task will be to combine the existing image reconstruction codes
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at NSLS-II seeks a postdoctoral researcher with a strong background in computational imaging, data science, or scientific computing. This position will focus on developing advanced image reconstruction
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: Qualifications required: The candidate must have a PhD's degree in Biophysics, Biology, Bioengineering or equivalent. Expertise in image/data analysis and coding is required (Python, Image J). Experience in cell
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mouse model of an ASD subtype. Responsibilities include stereotactic surgeries, viral vector manipulation, in vivo electrophysiology, opto/chemo-genetic experiments, behavioral testing, confocal imaging
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(e.g., PyTorch, TensorFlow, JAX), and scientific libraries (e.g., NumPy, SciPy, scikit-learn) Familiarity with medical images such as x-ray, CT, or fluoroscopy. Proficiency in Python coding language and
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implement cutting-edge AI solutions for real-time, image-guided medical applications, with a focus on advanced robotics. You will work directly with clinical data to design robust, efficient deep learning
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multitechnique approach, using ion beam imaging/spectroscopy, for example. In this context, the postdoctoral associate will be in charge of developing an operando/in situ cell compatible with ion beam analysis