Duties include:

Lead analyses of longitudinal epidemiologic and molecular data. Develop and apply statistical approaches for metabolomics, proteomics, and related high-dimensional data. Prepare first-author manuscripts and scientific presentations. Collaborate with epidemiologists, biostatisticians, clinicians, and laboratory scientists.

FLSA:

Exempt Salary Details $63,968

Minimum Salary:

20,000

Mid Range Salary:

90,000

Maximum Salary:

200,000 Offer Information The final salary offer may be determined by several factors, including, but not limited to, the candidate's qualifications, experience, and expertise, and availability of department or grant funds to support the position. We also take into consideration market benchmarks, if and when appropriate, and internal equity to ensure fair compensation relative to the university's broader compensation structure. We are committed to offering competitive and flexible compensation packages to attract and retain top talent. Benefits Rutgers provides a comprehensive benefits package to eligible employees. The specific benefits vary based on the position and may include: Medical, prescription drug, and dental coverage Paid vacation, holidays, and various leave programs Competitive retirement benefits, including defined contribution plans and voluntary tax-deferred savings options Employee and dependent educational benefits (when applicable) Life insurance coverage Employee discount programs

Position Status:

Full Time Working Hours 37.50

Standard Hours:

37.50

Daily Work Shift:

Day Union Description:

Post Docs -

Regular Salaried Payroll Designation:

PeopleSoft Terms of Appointment:

Staff - 12 month

Position Pension Eligibility:

ABP Required Knowledge, Skills, and Abilities Doctoral degree in epidemiology, biostatistics, public health, population health, or a related quantitative field by the position start date Applicants in All But Degree Status will be considered for interviews. Strong quantitative and epidemiologic training Experience conducting statistical analyses in R or a comparable programming environment Experience working with complex or high-dimensional health data Demonstrated ability to communicate scientific findings through manuscripts, presentations, or other scholarly products Interest in life-course epidemiology, the developmental origins of health and disease, pregnancy and perinatal health, or cardiometabolic health Ability to work both independently and collaboratively within an interdisciplinary research team Preferred Qualifications Experience analyzing metabolomics, proteomics, lipidomics, transcriptomics, or other high-dimensional molecular data Familiarity with methods such as dimension reduction, clustering, penalized regression, multiple-testing correction, pathway analysis, network analysis, or multiomics integration Experience with longitudinal cohort studies, pregnancy or birth cohorts, electronic health record data, or repeated-measures analyses A record of peer-reviewed publication and interest in developing an independent research program Candidates do not need to have experience in every preferred area. Applicants with strong epidemiologic and quantitative training who are interested in expanding their expertise in omics and life-course research are encouraged to apply.

Regional Campus:

Rutgers Biomedical and Health Sciences (RBHS)

Home Location Campus:

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