We are seeking to hire a full-time Sr. Biostatistician for the Johns Hopkins University research unit of multidisciplinary work-group, Data Integration and Analysis in Large cohorts and Biobanks (DIALB) as well as affiliated studies and faculty.
Specific Duties & Responsibilities
The DIALB group is a multidisciplinary group of investigators including senior faculty from biostatistics, human genetics, epidemiology, and medicine.
This position will entail:
Defining and maintaining an efficient computing and data environment which facilitates collaboration and secure access by a multidisciplinary team of faculty, staff, and trainees;
Integration of large cohort and biobank datasets, including –omic data (genomics, epigenetics, proteomics, metabolomics);
Assisting in the interpretation and writing of statistical results for manuscripts and other reports;
Assisting in developing, writing and implementing statistical analysis plans;
Active collaboration with investigators of DIALB to design analyses of study data for papers, grants, and presentations;
Collaboration with statisticians involved in DIALB regarding study designs and analyses;
Implementation of novel analytic methods in collaboration with faculty in the Department of Biostatistics;
Participation in regular seminars and meetings of DIALB investigators.
The ideal candidate for this position will have outstanding programming and organizational skills and the ability to learn and apply statistical algorithms to a range of large datasets, as well as a strong interest in collaborative epidemiologic and biostatistics research. A strong computing and mathematical background and the ability to learn new techniques rapidly incorporating innovative methods is a high priority. Data structuring skills are extremely important. The position will be based in the School of Public Health with the physical location in the Welch Center for Prevention, Epidemiology and Clinical Research (http://www.jhsph.edu/welchcenter). The analytic core is based the Welch Center, is affiliated with the Cardiovascular Epidemiology Training Program (www.jhsph.edu/cvdepi) and the Renal Disease Epidemiology Training Program, and has strong ties to multiple departments and other training programs at Johns Hopkins. Data sources include but are not limited to:
The ARIC Study: The ARIC Study has collected data from nearly 16,000 participants at four sites examined multiple times with a ~30-year follow-up over multiple visits. The primary research topics are in heart disease, kidney disease, and diabetes although investigators utilize these data for a broad range of topics. The study includes a large number of ancillary grants including genetic research. Core investigators of the Johns Hopkins ARIC Study research unit have faculty appointments in the Schools of Public Health and Medicine (~50 investigators and students at Hopkins collaborate with other sites; ARIC publishes >100 papers a year with ~10-30 per year led by Hopkins investigators). Specific work on this study will include integration of genetic (SNP arrays, whole exome sequencing, whole genome sequencing), longitudinal proteomic, metabolomic, and epigenetic data with rigorous collection of phenotype and outcome data on >10,000 ARIC participants.
Chronic Kidney Disease Prognosis Consortium (CKD-PC): CKD-PC uses state-of-the-art analysis methods to address pressing questions needed to optimize CKD care and research. The consortium comprises ~200 investigators from over 70 cohorts world-wide; new cohorts join each year. With estimated glomerular filtration rate (eGFR) and albuminuria measures in >11 million participants representing general, high cardiovascular risk, and CKD populations, the CKD-PC has a track record of producing high impact papers (Lancet, JAMA, NEJM). The consortium continues to work on advancing knowledge related to chronic kidney disease complications such as cardiovascular disease including peripheral arterial disease, end-stage renal disease and acute kidney injury.
External omic datasets: The UK Biobank (https://www.ukbiobank.ac.uk/) as well as external omic databases, such as genomics expression databases will be imported and used for further interrogation, validation, and meta-analysis to provide evidence for definitive papers integrating statistics and biology.
Master's degree in biostatistics, epidemiology, or related quantitative field.
Three years of related experience required.
Demonstrated ability on significant graduate project or additional doctoral education may substitute for experience to the extent permitted by the JHU equivalency formula.
Experience in programing required; SAS, Stata, R, Python, and/or other or the ability to learn them rapidly.
Candidates should have excellent communication skills and collaborative research experience.
Preferred 5 or more years of data management experience, requiring advanced skills with Stata, SPSS, SAS, or R.
Special Knowledge, Skills, and Abilities
Experience in statistical analysis using Stata, SAS, R, Python, SQL, and/or other statistical package is required
Technical qualifications or specialized certifications: None beyond the experience with statistical software.
Classified Title: Sr. Biostatistician Working Title:Sr. Biostatistician Role/Level/Range: ACRP/04/ME Starting Salary Range:$80,000 - $100,000; Commensurate with experience Employee group: Full Time Schedule: Monday-Friday, 8:30am - 5:00pm Exempt Status: Exempt Location: 05-MD:School of Public Health Department name: 10001101-Epidemiology Personnel area: School of Public Health
The successful candidate(s) for this position will be subject to a pre-employment background check.
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