55 engineering-"https:" "https:" "https:" "https:" "Data driven Materials Modeling" Postdoctoral positions at Yale University
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offers a vibrant scientific community and outstanding core facilities to support advanced genome engineering, imaging, and high-throughput sequencing. How to Apply Please submit the following materials
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, and therapeutic engineering. Projects may involve immunotherapy models, CRISPR-based perturbation and screening, mRNA therapeutics and vaccines, protein engineering, systems immunology, and tumor
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, while also playing a key role in the day-to-day operations of a dynamic team of faculty, research scientists, and students committed to advancing LGBTQ mental health through research (https
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submit application materials electronically to Interfolio at https://apply.interfolio.com/178923 . The review process will begin January 5, 2026. We will continue to accept applications until the position
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available. (https://postdocs.yale.edu/postdocs/being-a-postdoc-at-yale/postdoctoral-compensation ) Application Instructions Yale University will use Interfolio to search for this position. Applicants receive
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, and molecular profiling to link circuit activity to behavioral and physiological phenotypes. Qualifications Ph.D. (or equivalent) in neuroscience or a closely related field (e.g., biomedical engineering
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and kinetic modeling. A PhD in biomedical engineering, physics, or a related field is required. However, interested candidates with a strong computational background and interest in getting involved in
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debates, nationally and internationally, on digital ethics broadly understood. Proven research experience in digital ethics, technology policy, or the societal implications of digital technologies. A strong
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applied science on enhancing natural Earth systems to create safe, effective, and scalable methods of reducing greenhouse gas concentrations in the atmosphere. The YCNCC mission strongly emphasizes
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We are seeking a postdoctoral associate in intersectional feminist Science and Technology Studies. Preferred focus areas: critical computing/artificial intelligence studies; labor and automation