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focuses on applying modern causal inference and machine learning methods to observational EHR data. This role offers substantial opportunities for first-author publications, close mentorship, and increasing
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writing sample (e.g., first-author publication or preprint with related analysis code) demonstrating relevant experience and 3 professional references. Stanford is an equal opportunity employer and all
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in applied policy research. The fellow will have opportunities to co-author papers, present at conferences, and collaborate with faculty and graduate students across Stanford. Applicants should submit
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Qualifications: A PhD in biology, neuroscience, development, or a related field. At least one first-author publication. Experience with iPS cells is preferred but not mandatory. Required Application Materials: CV
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to our lab). Your curriculum vitae. Names and contact information to three reference writers. Stanford is an equal opportunity employer and all qualified applicants will receive consideration without
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-author papers and present at conferences with the goal of helping the Fellow continue to build out a robust program of research. Timeline Application review will begin January 30, 2025. Applicants
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involved in the project. Co-author high-impact peer-reviewed publications. Develop creative non-academic outputs to ensure findings are accessible and actionable for diverse communities. Required
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) Preparing publications and conference presentations (both collaboratively and as lead author) Building and maintaining research/community partnerships Supervising and mentoring other team members in the above
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editing, PCR, Sanger sequencing Track-record of first-author publications in reputable peer-reviewed journals Demonstrated self-initiative and motivation, ability to collaborate, organize parallel
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‑author high‑impact manuscripts and present at international conferences. • Mentor junior scientists and help shape the intellectual culture of the lab. Position Details • Location: Stanford University