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hospital environment. Responsibilities and qualifications The principle responsibility of the postdoc is to implement an improved processing pipeline for SURE and ULM imaging, which can be used in both a
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researcher will carry out research tasks in IMAG, within the ERC NEMESIS project team, led in IMAG by two principal investigators, Jérôme Droniou (CNRS) and Daniele Di Pietro (University of Montpellier
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. Proficiency in programming and data analysis. Experience in imaging/microscopy is an asset. Autonomy, rigor, creativity, team spirit, and strong communication skills. Additional Information Selection process
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optimization of optical imaging hardware, develop data acquisition software and algorithms for data processing, as well as perform phantom and human clinical studies. This candidate is expected to co-supervise
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computer clusters and french HPC time. COSMOS-Web is an international team of >100 permanent researchers, post-docs, PhD students, mainly in the US and Europe. The successful candidate will be in contact
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advanced machine learning methods for multimodal and 3D medical image analysis in musculoskeletal medicine, in close collaboration with clinicians and computer scientists. PhD or Postdoctoral Researcher
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single-element SNSPDs as well as kilopixel-scale imaging arrays which have high efficiency in the 2 – 16 µm wavelength range for applications in single-photon spectroscopy. The imaging arrays will be
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of the following areas: Image processing, partialdifferential equations, scientific computing, deep learning.•Solid programing skills. Knowledge of Python, Tensorflow/Pytorch, and Mathematica.•Fluent
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/developmental-neurobiology-and-regeneration/ Job Description Education & Qualifications • Bachelor’s degree in Biosciences or a related field • PhD in Neuroscience, Biomedicine, or a related discipline • Valid
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Radboud University Medical Center (Radboudumc); yesterday published | Netherlands | about 2 hours ago
Image Analysis Group (DIAG) at Radboudumc. We develop, validate and deploy novel medical image analysis methods, usually based on the newest advances in machine learning with a focus on computer-aided