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  2. Hyperspectral compressive imaging using deep convolutional neural networks

Hyperspectral compressive imaging using deep convolutional neural networks

The goal of this project is to demonstrate the feasibility of compressive fluorescence imaging, with the development of both the optical instrumentation and the deep learning-based reconstruction algorithms. The PhD position is funded for three years, starting in October 2019. It includes €5k support for travel and conference registrations. The applicant must hold a master's degree in optics and photonics, applied mathematics, or machine learning with a strong interest in medical imaging and programming.

Date: October 2019-September 2022

Salary: €1,850 gross monthly

More information: link

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sujet de thèse

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Recrutement passé

Periode

2019-2022

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