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pathogens as a model system. There are two post-doctoral research positions and one PhD studentship associated with Dr. McDonald’s UKRI Future Leader Fellowship, which will explore the cell biology
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(multiomics), CRISPR genome editing, deep learning, network modeling, confocal and two-photon live imaging. Please visit the Özel Lab Website for more information. Ideal candidates will be highly motivated and
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computational models with microbiome-driven mechanisms and lay the groundwork for studies on microbiome modulation as a therapeutic strategy. Integrating clinical expertise and advanced molecular analyses ensures
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electrophysiology to translational models, including animal studies and analyses of human tissue samples. This full-stack methodology enables us to directly link molecular channel function with disease phenotypes
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-scale screens to study fundamental principles in molecular and complex trait genetics using microbes as model systems. Our core technology MAGESTIC (https://doi.org/10.1038/nbt.4137 ), a CRISPR/Cas9-based
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assess their responses by cellular and molecular biology techniques;Establish and characterise human iPSC-derived cell models, including 3D cultures and organoids for musculoskeletal disease research
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injection, ion transfer, and structural dynamics in realistic and model systems for battery materials. The position will span experimental efforts at large scale X-ray facilities, handling and reduction
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modeling. Experience in cell culture, molecular cloning, and bioinformatics analyses is required. Proficiency in statistics and programming are highly meriting, especially in gene regulatory networks
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uniquely conserved—TRIM in animals and polyD/E in eukaryotes—setting them apart from classical PQC mechanisms. We are exploring their molecular mechanisms, their roles in aging and neurodegenerative diseases
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will develop innovative and generalizable methods and tools that can be applied to the in-house molecular data in pediatric cancers, such as pediatric CNS tumors and leukemias. St. Jude leads the largest