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Description The Buckler/Romay Lab at Cornell University is seeking a Postdoctoral Associate to advance research on maize and grass molecular diversity using genomic large language models (AI). The goal is to
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The Opportunity: Conduct research in Natural Language Processing (NLP), Computer Vision, and Artificial Intelligence (AI), with the goal of publishing in top-tier conferences such as CVPR, ICCV
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disease. Key responsibilities Lead and conduct the processing and statistical analysis of large-scale long-read RNA and DNA sequencing, single nuclei RNA sequencing and spatial transcriptomics
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. Evidence of scholarly productivity, including peer-reviewed publications or strong potential for publishing research. Effective written and oral communication skills, including the ability to communicate
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Zellers, DPT, PhD (jzellers@wustl.edu ) for more information. Materials to send to Dr. Zellers and to submit through the electronic submission system are: Cover letter. Curriculum Vitae including
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accordance with the Boston University Postdoctoral Compensation Guidelines and the Postdoctoral Scholars Policy. To be considered, applicants must hold a PhD in epidemiology, biostatistics, computational
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preprocessing, integration, and harmonization. Lead and contribute to manuscripts for high-impact journals and conferences (e.g., Nature-like journals or top CS conferences). Present findings in internal meetings
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that explain, guide, and support scientific data exploration without replacing human judgment Design human-centered interaction models for AI-assisted visualization, including natural language, mixed-initiative
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an interdisciplinary environment, possess excellent written and spoken English skills, and hold a PhD in a relevant discipline. The term of appointment is based on rank. The ideal start date is in early 2026, with
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, Neurodegeneration, PLINK (Software), Python (Programming Language), Statistical Genomics, Work Collaboratively Questions For frequently asked questions about the application process, please refer to our External