Visiting Biostatistician - Division of Endocrinology, Diabetes, and Metabolism

University of Illinois Chicago•Chicago, IL

23h•Onsite

About The Position

The Visiting Biostatistician will mainly work with the Division of Endocrinology, Diabetes, and Metabolism. The Visiting Biostatistician will be involved in all states of the research process, and provides study design, data management, statistical analysis, quality assurance, and study management services to a broad array of cardiometabolic research, including multi-omics, clinical, preclinical, epidemiological, and translational studies, in addition to review of protocols and grant applications. The Visiting Biostatistician will work under the guidance and in collaboration with Endocrinology faculty, and will provide statistical data support on design, analysis, interpretation and implementation to investigators for research/trial activities.

Requirements

Master's Degree in Biostatistics, Statistics, Bioinformatics, or related field required.
At least one year of related and recent experience in the analysis of quantitative research data within an academic environment required.
Must have experience analyzing high-dimensional multi-omics data using high performance computing clusters and cloud computing environments;
At least 1 year of experience in research and the integration of statistics application in biological principles.
Experimental design including basic science, population-based science, biological sciences and/or clinical trial studies addressing issues such as sampling recruitment, allocation of treatment(s), randomization strategies, and development of an analytic plan.
Thorough knowledge of applied aspects of longitudinal data analysis, including survival analyses and mixed modeling approaches, along with research data management using softward such as RedCAP is required through a combination of academic training and work experience.
Experience in data management, cleaning and interrogating of data, and determine missing data elements as appropriate.
Demonstrated proficiency using SAS, R, Stata, SPSS, or other relevant statistical programs.
Computer skills using high performance computing clusters (in a linux/unix environment) and cloud computing, along with Microsoft Office (Outlook, Word, Excel & PowerPoint).
Proficient in preparing tables and graphs to present clinicaI data or research study results.
Demonstrated skills in time management and project management.
Strong focus on quality and timely delivery of work; ability to multi-task and work on concurrent projects.
Demonstrated interpersonal skills to develop and maintain effective professional work relationships with investigators in various disciplines.
Ability to work well autonomously and in team environment with a wide range of varying disciplines.

Nice To Haves

Experience with epidemiological data and omics data, such as epigenetics and metabolomics.
Experience with machine learning.

Responsibilities

Collaborate in the development of study designs, and specifically data processing and analytic protocols, for high dimensional multi-omics research of large epidemiologic studies. Analyses will include not only data cleaning and testing specific study hypotheses but utilizing AI/ML methods and performing sample size or power calculations.
Use statistical and medical understanding to appropriately perform and advise investigators in data collection, management and analyses for multi-omics and traditional epidemiologic studies (i.e., genome wide association studies, longitudinal cohort studies and randomized controlled trials); provide interpretation and documentation of scientific data analyses, creates summaries, and present results in written and verbal form to investigator(s).
Performs a range of activities to facilitate the design of research projects and clinical trials; Contributes data management of on-going longitudinal studies, dataset development, data analyses and interpretation for preparation and delivery of reports for peer-reviewed publication, grant proposal and application, and presentations.
Collaborate with investigator(s) to ensure that project/trial results and conclusions are presented accurately and without bias.
Clean, organizes and performs quality control of data in preparation for analyses; prepares and edits data summaries of data analyses.
Attend project meetings with faculty, principal investigators, research staff, and other relevant stakeholders; Serve on research related committees such as the Protocol Review Committee (PRC) and/or Data Safety and Management Committee (DSMC).
Retain all study data in accordance with sponsor requirements and university policies and procedures.
Partner with investigator(s) to jointly achieve objectives and timeliness.
Perform other related duties and participate in special projects as assigned.