Biostatistics is a division within the Department of Population Health Sciences, the flagship population health research department of Weill Cornell Medicine and NewYork-Presbyterian. The Division of Biostatistics seeks multiple full-time tenure-track positions at the rank of Assistant, Associate, or Full Professor. This is a full-time (100% FTE), 12-month service period position. Salary and rank will be commensurate with qualifications and experience.
The Department of Population Health Sciences is home to six divisions. The Department is multi-disciplinary with substantial research strengths across a variety of areas including health policy and economics, health data science and data analytics, health informatics, comparative effectiveness & outcomes research, healthcare delivery science, epidemiology, and biostatistics. The Division of Biostatistics is comprised of faculty and master’s level staff dedicated to careers developing, applying, and teaching the highest standard of biostatistical methods. Through education, scholarship, and collaboration, we strive for transformative impact on population health, clinical outcomes, and health services research to inform prevention and treatment strategies.
We are seeking outstanding individuals engaged in biostatistical research, including, but not limited to, data science, high-dimensional data analysis, clinical trials, or statistical learning methods. Successful candidates will be expected to (1) participate in collaborative research with members of the Department, investigators within Weill Cornell Medicine or New York-Presbyterian Hospital, and/or the greater scientific community, (2) engage in the Division/Department’s teaching program; including formal classroom teaching and mentoring of student research, (3) contribute to the Divisional/Departmental community by engaging in seminars and other Divisional/Departmental outreach activities, including serving on key committees; (4) maintain an established high-impact statistical research program supported by external grants, and (5) actively promote diversity, equality and inclusion in the Division and the field of biostatistics. Faculty in this Division will leverage the burgeoning status of New York City as the epicenter of clinical medicine, as well as a number of academic and clinical collaborators including the Sandra and Edward Meyer Cancer Center, Cornell Tech, Center for Health Equity, New York Genome Center, Englander Institute for Precision Medicine, and New York-Presbyterian, the premier healthcare system in New York City including New York -Presbyterian Brooklyn Methodist Hospital, and New York-Presbyterian Queens. Focus areas for collaborative work include, but are not limited to, image analysis, population science, cancer, and cardiovascular diseases.
QUALIFICATIONS. Candidates must have a PhD or ScD (or foreign equivalent) in biostatistics, statistics, or a related field. For ranks at the Associate or Full Professor levels, it is critical that they also have an established record of high-quality research, teaching, and independent funding.
APPLICATION INSTRUCTIONS. All applicants are asked to submit:
1. a cover letter describing what they see as their future potential contribution (e.g., scientific leadership, pedagogy, diversity) to the discipline and Division;
2. an up-to-date curriculum vitae detailing publication, teaching and funding history;
3. contact information for three (3) references.
Review of applications will begin on December 1, 2021, continuing until the position is filled. Please send the requested information to Dinika Mirpuri at firstname.lastname@example.org.
CONTACT INFORMATION. For questions, please contact Karla Ballman at email@example.com.
Diversity is one of Weill Cornell Medicine’s core values and is essential to achieving excellence in patient care, research, and education. We welcome applications from candidates who share our commitment to fostering a culture of fairness, equity, and belonging. Weill Cornell Medicine is an Equal Employment Opportunity Employer, providing equal employment opportunities to all qualified applicants without regard to race, sex, sexual orientation, gender identity, national origin, color, age, religion, protected veteran or disability status, or genetic information.