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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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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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is to integrate genetics, cell biology, genomics, and bio-computing to unravel plant biological processes and to further translate this knowledge into value for society. Please visit us at
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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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processing of the omics datasets will guide selection of differentially regulated key genes to be evaluated for their therapeutic potential in our YARS1 Drosophila and iPSC models. Guided by the unmatched
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block within this process. You will be embedded both within an experimental and computational team, providing a unique atmosphere where there is expertise to develop the deep-learning models while having