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pharmacology, and in vivo calcium imaging (fiber photometry). Candidates should have experience or a strong desire to learn ex vivo electrophysiology. Position Sponsorship Eligibility: Not eligible for work
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proposals. Requirements Applicants with a Master’s degree in Computer Vision, Deep Learning, Computer Science, Image Processing, Biomedical Engineering, or related fields will be considered for the position
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the internal application process. Welcome to The Ohio State University's career site. We invite you to apply to positions of interest. In order to ensure your application is complete, you must complete
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carry out experimental protocols adapted to various samples (biological, material). Ensure advanced data processing and analysis (spectra, images, mappings). Maintain, improve, and ensure the smooth
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learning/computer vision methodology. The focus of this project will be on the development of deep learning methodology for spatio-temporal medical image analysis, that is medical images that evolve over
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Position: Our laboratory is recruiting a postdoctoral fellow to investigate how senescent cells shape tissue function in vivo, particularly its interplay with cellular plasticity/reprogramming
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. You will be co-supervised by Dr. Vassilis Sitokonstantinou and Prof. Ioannis Athanasiadis. Where to apply Website https://www.academictransfer.com/en/jobs/360046/phd-position-trustworthy-ai-and
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Researcher Profile Leading Researcher (R4) Positions Research Support Positions Application Deadline 6 Apr 2026 - 23:59 (Europe/Malta) Country Malta Type of Contract Temporary Job Status Part-time Hours Per
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PhD student at ILL on Advanced Neutron Imaging for Defect Mapping in Repaired Aero-Engine Components
underexplored. The aim of this PhD project is to develop and apply advanced neutron imaging methodologies in order to establish quantitative links between processing conditions, microstructural evolution
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to explore include mono-chromatic and multi-chromatic illumination, structured illumination, and telecentric illumination distortions. Computer based image analysis approaches will be developed, including