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CANDIDATES ONLY About Us The applicant will join the Imaging Machine learning And Genetics in Neurodevelopment (IMAGINE) lab, in the Research Department of Biomedical Computing. We are a highly collaborative
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magnetic microscopes for contactless imaging of the magnetic field induced in biological tissue samples. Our aim is to build the world’s fastest, most sensitive microscope capable of resolving magnetic
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parasite mutants, antibodies, spatial proteomics, real-time and super-resolution imaging, we will reveal essential protein domains and characteristics, will identify interacting protein partners and will
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of an additional second year contingent upon funding and performance. Individuals with a PhD in political science, computational social science, or a cognate discipline are encouraged to apply. Preference will be
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workflows (e.g., Kilosort, SpikeInterface) and neural data quality control Experience with imaging data processing, anatomical or functional registration, and 3D planning/reconstruction for recording
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at the forefront of nano-optics and nanophotonics within the Vectorial Nano-Imaging research unit at Istituto Italiano di Tecnologia, led by Dr. Antonio Ambrosio. The research activity focuses on the investigation
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troubleshoot each specific procedure as required • Assist and train other members of the laboratory, including undergraduate and graduate students, in proper experimental technique and in following protocols 15
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Regular Job Code 9546 Employee Class Acad Prof and Admin Add to My Favorite Jobs Email this Job About the Job Utilize multi-photon optical imaging to study neuro-vascular coupling in the mammalian brain
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The Department of Medicine at the University of Virginia is seeking a Postdoctoral Research Associate to work in the laboratory of Dr. Jeffrey Sturek, MD, PhD. The Sturek Laboratory is an exciting
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Postdoctoral position in the development of an AI-based phenotyping system for high-throughput sc...
work. Qualifications PhD in computer science, computational biology, engineering, or related fields. Experience developing deep-learning tools for image processing, automatic monitoring of agricultural