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Field
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signaling in larval Drosophila using two-photon tracking microscopy developed in the Gershow lab. The postdoctoral researcher will design and conduct imaging experiments, analyze volumetric imaging datasets
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Chekouo and his collaborators within and outside the University of Minnesota. The research will focus on the development of Bayesian statistical/machine learning methods for the data integration analysis
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an advantage Strong background in machine learning for image analysis and computer vision, ideally involving microscopy, time-lapse imaging, or other high-dimensional scientific imaging modalities
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national Scientific Society meetings. Minimum Education and/or Work Experience M.D. or PhD Required Qualifications M.D. or PhD Required Certificates/Credentials/Licenses N/A Computer Skills General office
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strands. • Bespoke modelling of tumour metabolic function using 3D and 4D imaging data • Cancer patient risk prediction using machine learning (with experience in particular in radiomics and transcriptomics
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 2 months ago
-tier machine learning and computer vision venues, actively participating in departmental seminars, and contributing to collaborative projects. Where to apply Website https://jobs.inria.fr/public/classic
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 2 months ago
simulation, shape/topology and system-level design optimization applied to deformable systems — advanced level Data-driven design and modelling approaches (machine learning applied to physical/mechanical
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to, flow cytometry, ELISA, RT-PCR, bulk and single cell RNA sequencing, imaging and other emerging technologies (e.g. imaging mass cytometry, spatial transcriptomics, metabolomics/proteomics) – including
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Post Doctoral Researcher Rinn Artificial Intelligence – Research & Innovation in Data Science and AI
techniques. This strand would involve adapting in-house models for Positron Emission Tomography data to other imaging modalities. Research in the other strands that focus on machine learning applications will
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biofluid samples Conceive, prototype, and benchmark new computational and AI methods for liquid biopsy, including techniques to bridge to other data modalities, e.g. imaging Apply modern machine learning