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opportunity to develop cutting-edge AI-enhanced algorithms for analyzing transposable elements (TEs) in cancer epigenomics, with direct translational applications to precision oncology and immunotherapy
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of computational biology, Genomics, machine learning, and data science, contributing to the development and evaluation of advanced algorithms for analyzing large-scale biological datasets. This role is ideal
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interdisciplinary and collaborative group, and a track record of publications. The candidate must also be willing to mentor students. Previous experience in evolutionary developmental biology and non-bilaterian
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