Research - Laboratory/Non-Laboratory, Staff/Administrative
The Research Data Analyst will conduct qualitative analysis 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. The DIALB group is a multidisciplinary group of investigators including senior faculty from biostatistics (Dr. Nilanjan Chatterjee), human genetics (Dr. Dan Arking), epidemiology (Dr. Josef Coresh), and medicine (Dr. Morgan Grams). 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 Department of Genetic Medicine and has strong ties to multiple departments and other training programs at Johns Hopkins.
Specific Duties and Responsibilities:
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.
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.
Minimum Qualifications (mandatory):
Bachelor's degree in related discipline.
3 years related experience.
Additional education (Mater’s level) may substitute for require experience to the extent permitted by the JHU equivalency formula***.
Degree in computer science, math, biostatistics, statistics, epidemiology, biomedical engineering, or quantitative field desirable,
Experience in programing SAS, Stata, R, Python, and/or other or the ability to learn them rapidly.
Collaborative research experience.
Special Knowledge, Skills, and Abilities:
Excellent communication skills.
***JHU Equivalency Formula: 18 graduate degree credits may substitute for one year of experience. For jobs where equivalency is permitted, up to two years of non-related college course work may be applied towards the total minimum education/experience required for the respective job.
Classified Title: Research Data Analyst Working Title: Research Data Analyst Role/Level/Range: ACRP/04/MC Starting Salary Range: $45,195-62,225 (commensurate with experience) Employee group: Full Time Schedule: Monday-Friday/8:30am-5:00pm Exempt Status: Exempt Location: 04-MD:School of Medicine Campus Department name: 60000577-SOM Genetics Arking Personnel area: School of Medicine
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