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genomics and live-cell imaging, we can now explore hormone regulation at unprecedented single-cell resolution. Using these tools, we have observed dynamic fluctuations in brassinosteroid signalling
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of the cell cycle. With the advent of advanced technologies, such as single-cell genomics and live-cell imaging, we can now explore hormone regulation at unprecedented single-cell resolution. Using these tools
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candidate eager to operate at the interface of molecular biology, neuroscience, and AI. Responsibilities Wet-Lab & Experimental Work Set up and optimize imaging based spatial transcriptomics protocols. Set up
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, regulatory networks and/or interaction networks; computational modeling of cell morphology, tissue organization, and organ function using biomedical imaging and computer vision techniques. These research
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modeling of biomolecule structures, regulatory networks and/or interaction networks; computational modeling of cell morphology, tissue organization, and organ function using biomedical imaging and computer
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from prototype to user-friendly instrument Communicate with scientists to facilitate the experimental setup and the possible traits Contribute to a collaborative and productive team environment
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Programming experience in Python Excellent communication skills and fluency in English Collaborative personality with attention for detail Bonus but not required Experience in imaging or spatial omics data
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at the cellular level, and (iii) applying quantitative image analysis to compare structural organization across fertile and infertile donors. The project is embedded in an active collaboration with a local
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field Proven ability to lead technically complex projects Practical experience in cryo-EM/cryo-ET and/or subtomogram averaging, or outstanding computational skills applied to imaging data
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support: assist researchers in performing histology (sectioning, staining, imaging), molecular biology, flow cytometry, and cell culture; maintaining accurate documentation (protocols, SOPs, results