345 data-"https:"-"https:"-"https:"-"https:"-"https:"-"U.S"-"U.S" Fellowship positions in United States
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Field
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surrounding building such an experimental toolkit; from the ultrafast optics to the spatial resolution and statistical data analysis. Basic Qualifications PhD in Physics, Chemistry, Biology, Mathematics and
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, data science, civil engineering, or a related field, with research expertise in geospatial artificial intelligence, human dynamics, and/or urban informatics. Candidates will need to have completed
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an in depth knowledge of a specialized field, process, or discipline and may involve organizing and implementing complex research plans, the development of methods of research, testing and data collection
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online portfolio is appreciated. A list of references should be submitted along with the resume and the contact information of no less than three reviewers. Contact Information Evie Santana-Nola Contact
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names and contact information of three references. Harvard University is committed to equal opportunity and non-discrimination . We seek talent from all parts of society and the world, and we strive
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Responsibilities Perform CAR T cell generation and functional assays under guidance of senior lab members Conduct flow cytometry–based immune phenotyping and cytokine analyses Analyze and interpret data from
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career development. For more information about Dr. You’s lab, please visit here. As a successful candidate, you will: Lead independent and collaborative projects investigating the molecular and cellular
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. Must have experience with analysis of sequencing data (RNA-seq, CUT&RUN, etc) and/or sufficient computation background to learn these analyses. Must have a strong publication history supporting potential
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the persuasive capabilities of AI systems and the risks they pose to the information ecosystem. Core responsibilities include: Advancing research on the risks of AI-driven persuasion within the information
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, including other Harvard Medical School-affiliated hospitals. The qualified candidate will analyze multi-omics liquid biopsy data for minimal residual disease (MRD) detection, quantification, and assessment