45 parallel-and-distributed-computing-"Meta"-"Meta" positions at Cold Spring Harbor Laboratory
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experiments, including: Massively parallel reporter assays (MPRAs) Protein deep mutational scanning (DMS) assays CRISPR interference (CRISPRi) screens Genomic base-editing screens These experiments will be
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, including the Summer Internship for Medical Students, the MD/PhD Program, and the Translational Research Training Fellowship. • Maintain and update the affiliation webpage and related email distribution lists
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are expected to have a PhD in Physics, Mathematics, Computer Science or a related quantitative discipline. Ideal candidates from the biological sciences should have experience with scientific programming. Ideal
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massively parallel reporter assays (MPRAs) and CRISPR interference (CRISPRi), to investigate the regulatory genomic elements (enhancers and promoters) that control gene expression across various cell types
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on distribution of content. Collaborate with internal teams to provide support in marketing campaigns, donor outreach, and various other organizational initiatives. Maintain a consistent, professional, and engaging
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environment and pay attention to details. Must be highly organized, and able to multitask. Excellent communication and interpersonal skills. General computer skills. 5 years of histology experience is required
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Position Description Cold Spring Harbor Laboratory (CSHL) is seeking to fill a Cold Spring Harbor Laboratory Fellow position in the area of NEUROSCIENCE (experimental and/or computational
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Position Description CSHL is seeking outstanding graduate students in Artificial Intelligence to spend the summer at CSHL as NeuroAI Interns, part of an innovative new program at the intersection
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its renowned Meetings and Courses program. We believe that science is for everyone and our researchers have a wide variety of backgrounds. Compensation and Benefits Our employees are compensated in many
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and the microbiome affect tissue fitness or cancer outcomes. We utilize state-of-the-art experimental and computational approaches to integrate genetic, epigenetic, metabolism and microbiome data