Open Rank Associate Professor/Professor in Data Science

• Serve as a key leader in developing all data-related aspects of a well phenotyped dementia risk cohort.
• Provide leadership in ensuring robust data analysis protocols.
• Lead a program of federally funded, data-driven research in Alzheimer’s disease and related dementias that will contribute to the development of, and leveraging of the research cohort, in order to better understand the mechanisms and risk factors associated with Alzheimer’s disease.
• Lead and collaborate on manuscripts using cohort data.
• Oversee the collection, curation, and management of clinical, genetic, imaging, digital and biomarker data.
• Develop predictive models and algorithms to identify risk factors, disease markers, and potential therapeutic targets for Alzheimer’s disease.
• Implement machine learning models to improve prediction, diagnostic accuracy and monitoring of disease progression.
• Lead and contribute to grant proposals that support future funding of cohort data collection and address research questions of high scientific and public health importance in Alzheimer’s disease and related dementias.
• Successfully compete for extramural funding
• Participate in mentoring, training, and professional development of staff, post-doctoral fellows, junior physicians, students, and others collaborating on the cohort study.

JOB REQUIREMENTS:
To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

• Experience in utilizing advanced statistical and machine learning techniques and interpreting findings to identify new Alzheimer’s Disease and related dementias (ADRD) research directions.
• Ability to develop and lead a program of independent federally funded research including a record of leadership of, or contributions to, major successful peer-reviewed grant proposals appropriate to the applicant’s academic rank.
• Candidate must possess good understanding of informatics infrastructures to support highly innovative research within high performance computing (HPC), cloud computing, and secure computing environments.
• Experience in cross platform and user friendly applications development to support high volume heterogeneous data processing, structures, integration, analysis, management, and sharing.
• Knowledge in learning healthcare systems and expertise in clinical data extraction, transfer, loading, and de-identification.
• Academic credentials that qualify for appointment as an Associate Professor or Professor at Rutgers University including a record of successful extramural funding and peer-reviewed publications addressing Alzheimer’s disease and related disorders. Superb young investigators with NIH funding and a high potential for scientific independence and success will be considered.
• Record of successful multi-disciplinary collaboration and mentorship of students and early-stage investigators.
• Strong interest and enthusiasm in helping achieve successful implementation of the new cohort and contributing to cutting-edge science.
• Excellent written and oral communication skills and the ability to communicate research findings and concepts to both academic and non-academic audiences.