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Maze/UCSF Advanced Analytics Fellowship
We are seeking a passionate and talented Postdoctoral Researcher to advance the field of applied machine learning in the context of human genetic data. This individual will conceive and execute analyses clarifying the application of natural language processing models to diverse aspects of early biological target discovery and evaluation while embedded within a collaborative academic/biotech setting. Using large-scale transformer neural networks to model the effects of protein coding variation in the human genome, the successful candidate will lead the development of novel methodology to characterize disease relevance and lay the foundations for an ultra-high throughput experimental framework This position is supported by the


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