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, sequencing, automation, imaging, and bioprocessing. GBI will also have access to substantial compute resources that can be leveraged to further accelerate progress, including scientific compute, bioinformatics
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, and deep generative models (e.g., VAEs, normalizing flows, diffusion models). Hands-on experience in multi- and hyperspectral image processing (e.g., IDL/ENVI) and RTM inversion (e.g., ARTMO
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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
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ICT Services & Applications. Your role The successful candidates will join the Computer Vision, Machine Intelligence and Imaging research group, led by Prof. Djamila Aouada, to conduct research in
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(Thorlabs) for imaging large cortical and subcortical areas in awake head-fixed animals, two 2-photon microscopes for single-cell electrophysiological experiments in brain slices (Chun et al, Science 2014
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Essential criteria are: Doctoral degree in computed tomography, image analysis, or similar Demonstrated experience in programming (e.g., Python, MATLAB) Theoretical knowledge and practical experience in
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-EM sample preparation, data collection, and high-resolution structure determination • Process and refine complex cryo-EM datasets using strong computational skills (RELION, cryoSPARC, etc.) • Conduct
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Postdoctoral Fellow in innate immunity Employer: Mount Sinai School of Medicine Research lab: Teunissen lab Institute Biomedical Engineering and Imaging Institute PI: Dr. Abraham Teunissen Location
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various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly
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, the Division of Signaling and Functional Genomics at the German Cancer Research Center is seeking as soon as possible a Postdoc – Bioinformatics / Computational Biology Reference number: 2026-0007 The Division