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, tissues, and organs using antibody-based imaging, transcriptomics, and systems biology approaches. Since its launch, the atlas has generated one of the world’s most comprehensive open resources for spatial
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leading the investigation of structural and biophysical properties of miniaturized tumor environment models. A multidisciplinary approach is expected, integrating microfabrication, cell component and
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regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods, statistical analysis and efficient algorithm and data structures (https
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emphasis will be placed on personal characteristics such as creativity, thoroughness, a structured approach to problem-solving, and the ability to work both independently and in a team. Additional
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, thoroughness, a structured approach to problem-solving, and the ability to work both independently and as part of an interdisciplinary team. Additional qualifications Experience in simulation-based or likelihood
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structure – function relationships in lipid systems for drug delivery (predominantly lipid nanoparticles). The group has extensive expertise using large scale research infrastructures to study lipid systems
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a demonstrated interest in cell biology and biological modelling. Have experience interpreting biological datasets, particularly imaging data and multimodal datasets combining imaging and molecular
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. A central goal is to integrate spatial imaging data with time-resolved molecular measurements, while incorporating physical and biological constraints directly into the model architectures
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identity and extracellular signaling, but how cell types, signaling mechanisms, and transcription factors jointly determine tissue structure is incompletely understood. The Koplev lab is recruiting
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model organisms, their application in conifers remains limited due to challenges associated with tissue structure, nuclei isolation and sensitivity to inhibitory compounds. This project aims to develop