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in image processing, quantitative analysis, and biological interpretation Proficiency in AI/machine learning tools for image segmentation, transformation, registration, or tracking Solid mathematical
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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with ultrastructural analysis. Manage, process, and analyze large imaging datasets generated from the project. Assist in mentoring and training PhD and undergraduate students in relevant techniques and
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neurobiology and mouse models is advantageous. Have experience with in vivo calcium imaging (preferably 2-photon), stereotactic surgery and drug delivery, gene expression analysis (e.g. snRNAseq) and antisense
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neuroimaging experiments, proficient in image processing and programming paradigms. The successful candidate will contribute to ongoing multidisciplinary research and play an active role in developing novel
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programming languages such as C and Python Proficiency in deep learning frameworks such as Pytorch and Tensorflow Knowledge in imaging and computing device and equipment Good written and oral
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create a collaborative and engaged user community. A special focus lies on the operation of the multiphoton and FLIM microscopy systems and establish intravital imaging pipeline. Main Duties and
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conditions. To propose a methodology/framework in a software prototype to be developed in the project. To report research findings in the form of a report and present in international peer-reviewed conferences
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models using frameworks such as PyTorch and TensorFlow. Research experience in medical image analysis using deep learning algorithms. Strong track record in machine learning, computer vision, and medical