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Field
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Summary The primary research focus is the role of cell adhesion and neuronal self-avoidance in the developing mouse retina, focusing on two families of cell adhesion molecules: the clustered
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and uses these applications to inform new foundational ML and NLP innovations. The position provides unique access to world-class computing resources, such as the BNL Institutional Cluster and DOE
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-years to better understand innovation clusters and how to accelerate the quantity and quality of innovation output and their economic and social impact. This team will conduct research as part of
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(e.g. Python, R, …). Familiarity to work on a Linux computing cluster (HPC). Preferably experience in working with large medical image data. Vivid interest in the analysis of microscopy images or similar
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linear mixed models, and biological network analysis. This may require development of new computer algorithms and/or construction of computational workflows on computer clusters. The types of multi-omics
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to natcap_admin@stanford.edu (link sends e-mail) with “NATCAP POSTDOC CLUSTER HIRE” listed in the subject line. We will begin reviewing applications immediately and the positions will remain open until filled