NYU Langone Health
Assistant/Associate Professor, NYU Grossman School of Medicine: Optimal Aging In
NYU Langone Health, New York, New York, us, 10261
Overview
The Optimal Aging Institute at NYU Grossman School of Medicine is hiring faculty at the Assistant and Associate Professor levels. Candidates who are focused on the epidemiology of aging and/or age-related diseases, biomarkers, development and utilization of artificial intelligence methods, research using electronic health records or other human data, clinical trials, or clinical research are encouraged to apply. The candidate is expected to lead their own research programs as well as foster collaborations throughout NYU Langone Health. The Optimal Aging Institute’s mission is to advance the science of optimal aging and improve healthspan, allowing every individual to live with vitality, independence, and purpose throughout their lifespan. Leveraging population-based cohorts and epidemiologic research methods, our focus is on the prediction, prevention, detection and management of age-related diseases. Research performed in the Institute spans epidemiologic research in population-based cohorts and electronic health records, to multimodal analyses and the use of AI with the goal of identifying biomarkers and mechanisms of aging, and advancing translational research aimed at individualized prediction and prevention. As part of an integrated learning health system, interdisciplinary collaboration with clinical and basic science departments is key. Successful candidates must hold a PhD, DrPH, MD, or equivalent doctoral degree in relevant public health and population health fields such as epidemiology, biostatistics, data science, clinical informatics, or related disciplines. Candidates should demonstrate scholarship through publications, mentorship, teaching, and extramurally-funded research. The successful candidate must demonstrate interpersonal, written and oral communication skills to effectively communicate, collaborate, establish and maintain good working relationships with a multi-disciplinary team of researchers, faculty, staff, and partners. NYU Langone Health
is an equal opportunity employer and committed to inclusion in all aspects of recruiting and employment. All qualified individuals are encouraged to apply and will receive consideration. Responsibilities
Lead their own research programs and foster collaborations across NYU Langone Health. Contribute to interdisciplinary, learning health system initiatives with clinical and basic science departments. Engage in epidemiologic and translational research using population-based cohorts, electronic health records, or other human data; pursue clinical trials or clinical research as appropriate. Publish, mentor, teach, and seek extramural funding to support research activities. Qualifications
PhD, DrPH, MD, or equivalent doctoral degree in epidemiology, biostatistics, data science, clinical informatics, or related fields. Demonstrated scholarship through publications, mentorship, teaching, and extramurally-funded research. Strong interpersonal, written and oral communication skills; ability to collaborate with a multi-disciplinary team.
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The Optimal Aging Institute at NYU Grossman School of Medicine is hiring faculty at the Assistant and Associate Professor levels. Candidates who are focused on the epidemiology of aging and/or age-related diseases, biomarkers, development and utilization of artificial intelligence methods, research using electronic health records or other human data, clinical trials, or clinical research are encouraged to apply. The candidate is expected to lead their own research programs as well as foster collaborations throughout NYU Langone Health. The Optimal Aging Institute’s mission is to advance the science of optimal aging and improve healthspan, allowing every individual to live with vitality, independence, and purpose throughout their lifespan. Leveraging population-based cohorts and epidemiologic research methods, our focus is on the prediction, prevention, detection and management of age-related diseases. Research performed in the Institute spans epidemiologic research in population-based cohorts and electronic health records, to multimodal analyses and the use of AI with the goal of identifying biomarkers and mechanisms of aging, and advancing translational research aimed at individualized prediction and prevention. As part of an integrated learning health system, interdisciplinary collaboration with clinical and basic science departments is key. Successful candidates must hold a PhD, DrPH, MD, or equivalent doctoral degree in relevant public health and population health fields such as epidemiology, biostatistics, data science, clinical informatics, or related disciplines. Candidates should demonstrate scholarship through publications, mentorship, teaching, and extramurally-funded research. The successful candidate must demonstrate interpersonal, written and oral communication skills to effectively communicate, collaborate, establish and maintain good working relationships with a multi-disciplinary team of researchers, faculty, staff, and partners. NYU Langone Health
is an equal opportunity employer and committed to inclusion in all aspects of recruiting and employment. All qualified individuals are encouraged to apply and will receive consideration. Responsibilities
Lead their own research programs and foster collaborations across NYU Langone Health. Contribute to interdisciplinary, learning health system initiatives with clinical and basic science departments. Engage in epidemiologic and translational research using population-based cohorts, electronic health records, or other human data; pursue clinical trials or clinical research as appropriate. Publish, mentor, teach, and seek extramural funding to support research activities. Qualifications
PhD, DrPH, MD, or equivalent doctoral degree in epidemiology, biostatistics, data science, clinical informatics, or related fields. Demonstrated scholarship through publications, mentorship, teaching, and extramurally-funded research. Strong interpersonal, written and oral communication skills; ability to collaborate with a multi-disciplinary team.
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