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The Cleveland Clinic is searching for an Associate or Full Professor-level faculty member to join its multidisciplinary Department of Quantitative Health Sciences on the Cleveland Clinic main campus. This full-time faculty position offers a unique opportunity to contribute both collaboratively and independently with musculoskeletal researchers, spanning the range from basic and translational studies to sports medicine to orthopaedic surgery cohort studies and randomized trials, within a leading healthcare environment.
Position Overview
· Collaborative Research (70%): Design and analyze complex observational and experimental studies, including randomized clinical trials, in partnership with investigators from the Cleveland Clinic Department of Orthopaedic Surgery and Musculoskeletal Research Center.
· Independent Research (30%): Engage in independent research projects that advance the fields of biostatistics, epidemiology, data science, and their contributions to musculoskeletal research.
Key Responsibilities
· Collaborate with multidisciplinary teams of physicians, scientists, and engineers in musculoskeletal research.
· Lead and mentor a team of MS-level biostatisticians supporting musculoskeletal research.
· Develop and deploy data-intensive research studies, including the integration of diverse data sources (basic science, -omics, imaging, and patient-reported outcomes).
· Build data-driven models for patient phenotyping and outcome prediction using a wide range of modeling techniques, from classical statistical methods to artificial intelligence/machine learning and digital twinning.
Qualifications
· Education: Ph.D. in Statistics, Biostatistics, Epidemiology, or a related discipline.
· Experience: Demonstrated experience as a collaborative biostatistician in a clinical setting.
· Expertise:
- Clinical research design and statistical methodologies for cohort studies and clinical trials, including longitudinal data analysis, survival analysis, and modern statistical methods.
- Proficiency in machine learning, data mining, and advanced analytical methods for large-scale healthcare data.
- Experience with the integration and analysis of multi-source data is highly desirable.
· Leadership Skills: Strong leadership and collaborative abilities, with a desire to lead a biostatistical team.
· Communication Skills: Excellent written and oral communication skills in English. Enthusiasm for research in orthopaedic surgery, sports medicine, biomechanics, and related musculoskeletal research.
Appointment Details
· Funding: This is a hard-money faculty position with no explicit requirements to obtain additional external funding. However, a large portion of this individual’s effort will be in collaboration with musculoskeletal researchers to support extramurally funded programs, from which some external funding would be anticipated.
· Academic Affiliation: Non-tenured appointment at the Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, with rank commensurate with experience.
Interested candidates should email a curriculum vitae, the names of at least three references and a letter summarizing experience, research interests, and fit for the position to [email protected] Review of applications will begin immediately and continue until the position is filled.
Stephanie Kocian
[email protected]
Department of Quantitative Health Sciences is seeking a faculty Epidemiologist to lead collaborations with the Cleveland Clinic Integrated Hospital Institute, Department of Pulmonary Medicine to grow our emphasis in environmental epidemiology across the field of respiratory health. The ideal candidate will serve as a primary resource for existing research within the Cleveland Clinic System, while also engaging as an independent researcher to advance partnerships and collaborations with greater Northeast Ohio and improve the health of our community.
A doctoral degree is required. The position includes a non-tenured appointment to the Cleveland Clinic Lerner College of Medicine of Case Western Reserve University at rank commensurate with experience.
The ideal candidate would have a track record in environmental epidemiology research, with a skillset in modeling and exposure estimation of ambient or indoor air pollution, and a rigorous grounding in spatial epidemiology techniques. Independent grant funding is not a requirement. A background in the impact of environmental exposures on respiratory health is preferred, though not required.
Job Requirements
Preferred qualifications and experience:
· PhD in environmental health sciences, epidemiology, or related field
· Experience with modeling and exposure estimation of ambient air pollution
· Experience working with large datasets, including electronic medical record data
· Experience in spatial epidemiology and using GIS software such as ARcGIS
· Experience working in collaborative, multi-disciplinary research teams
This is a “hard money” position with the expectation of obtaining collaborative grant funding over time. A combination of collaborative and independent research is expected, with the majority of time dedicated to collaborative work.
Interested candidates should email a curriculum vitae, the names of at least three references and a letter summarizing experience, research interests, and fit for the position to [email protected].
Review of applications will begin immediately and continue until the position is filled.
Stephanie Kocian
[email protected]
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