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. Building on this platform, we combine cell biology, biochemistry, CRISPR-based approaches, organelle isolation, metabolomics and proteomics, mouse genetics, and disease models to discover principles of ER
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14 Jul 2026 Job Information Organisation/Company KU LEUVEN Research Field Computer science » Modelling tools Computer science » Programming Computer science » Systems design Technology » Computer
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that decouple the chemical and mechanical inputs to the receptor. Fit the model to experimental measurements acquired across decoupled conditions, attributing receptor activation to each input. Use the resolved
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physiology, animal models of cancer and cachexia, imaging, histological analyses, and other mechanistic or translational approaches. · Contribute to the development, optimization, and validation
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about working at the University of Arizona and relocations services, please Duties & Responsibilities Conduct immunohistochemistry staining to assess brain pathological changes in mouse models; whole cell
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with computed tomography and digital subtraction angiography. • Familiarity with reinforcement learning methods. • Experience developing and applying statistical models to research datasets. • Experience
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laboratory workflows. The position will focus on building the data resources, predictive models, and closed-loop decision frameworks needed to accelerate experimentation and advance next-generation autonomous
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cancer cell biology and tumor microenvironment, with experience in immunology and murine models. Candidate must be an expert communicator, highly organized, with excellent writing and grantsmanship skills
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has the potential to include (1) contributing to an NSF-funded research aimed at understanding disease dynamics in wildlife trade using amphibians as a model system, (2) leading research to investigate
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elegans (C. elegans) as a model system with approaches including: Quantitative genetics (GWAS/QTL mapping) High-throughput phenotyping RNA-seq and multi-omics integration Functional genomics (e.g., RNAi