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to drive the generation and analysis of data, to present at conferences, contribute to writing of papers and future grant applications. This is an exciting area of research using an in vitro model of human
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at the intersection of these research areas. You should hold, or be close to completing, a PhD/DPhil in mathematics, statistics, physics, engineering, data science, or a related field. Experience in cancer
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at the intersection of these research areas. You should hold, or be close to completing, a PhD/DPhil in mathematics, statistics, physics, engineering, data science, or a related field. Experience in cancer
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: D1. Skills in animal models Experience Essential: E1. Proven ability to deliver quality outputs (such as publications) in a timely and efficient manner. E2. Experience preparing data for publication
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responsibilities will include: Pre-registering data analysis plans; Leading and conducting advanced statistical analyses (e.g., twin/family designs, genomic and epidemiological methods, longitudinal modelling
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proteome in heart-specific cell lines and primary tissue. It will utilize disease model systems to characterize unique cell surface signatures for cardiomyocytes, coronary endothelial cells, and fibroblasts
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cytometry will be an advantage. The project has a major computational component both for AI-driven modelling and predictions, and for bioinformatics analyses of wet-lab data. This will be performed by
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, aquaculture breeding and production systems and disease resistance models will be appreciated. The position requires a self-motivated and highly organized individual with excellent communication skills
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evaluations, attacks on and defensive mechanisms for safe multi-agent systems, powered by LLM and VLM models. Candidates should possess a PhD (or be near completion) in Machine Learning or a highly related
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proteome in heart-specific cell lines and primary tissue. It will utilize disease model systems to characterize unique cell surface signatures for cardiomyocytes, coronary endothelial cells, and fibroblasts