JOB SUMMARY:

The Division of General Internal Medicine at the University of Colorado School of Medicine is seeking a Research Services Information Science Professional. This position will be with the Barocas Lab, an innovative, interdisciplinary research program that is aimed at studying the intersection of infectious diseases, substance use disorders, and social determinants of health. This research program uses a combination of clinical epidemiology, simulation modeling, machine learning, and health economics to 1) improve health outcomes for vulnerable populations, 2) uncover structural factors that drive health inequities, and 3) inform health policy.
Housed within this lab are several highly innovative programs including 1) The Missing US Project, a multi-state project aimed at uncovering hidden populations and hidden risk factors for substance use and HIV and re-defining epidemiologic surveillance systems using a community-engaged approach, 2) The ReDUCE Project, which uses simulation modeling to understand cost-effective strategies to reduce infectious complications associated with substance use, 3) Fentanyl Felonization Study, a state-funded project to understand the health effects of criminal penalties for drug use, and 4) the Health Economics Core for the HEALing Communities Study, a large-scale, multi-state intervention study to reduce opioid overdose deaths by 40%.
A person in this position will work alongside the principal investigator, research manager and several team members in several states in the analytic aspects of the research including data management, advanced statistical analyses, and simulation modeling. This is an open-rank recruitment; therefore, candidates are being considered at the entry, intermediate and senior levels depending on their qualifications.

PREFERRED QUALIFICATIONS:

• Master’s degree in Bioinformatics, Biostatistics, Computational Biology, Data Science, Computer Science, Epidemiology, Public Health, or related field
• One (1) to four (4) years of experience analyzing data and data modeling using high-performance computing.
• Experience in foundations of epidemiology.
• Experience with C++, python.
• Experience with simulation modeling.
• Experience serving vulnerable populations.

KNOWLEDGE, SKILLS, AND ABILITIES:

• Knowledge of basic statistical principles relevant in medical research.
• Database software expertise (proficient or advanced) including but not limited to R, STATA, or SAS,
• and RedCap, SQL.
• Ability to analyze and solve complex problems and apply quantitative analytical approaches.
• Demonstrated fluency in one or more programming languages (e.g., R, Python, Perl, Java, C++) and willingness to learn new programming languages as necessary.
• Basic knowledge of advanced mathematics (such as calculus).
• Familiarity with statistical analytical concepts and methods.
• Demonstrated passion for research focused on vulnerable populations.
• Ability to communicate effectively, both in writing and orally.
• Ability to establish and maintain effective working relationships with employees at all levels throughout the institution.
• Outstanding customer service skills.
• Knowledge of basic human anatomy, physiology medical terminology.
• Ability to interpret and master complex research protocol information.
• Ability to work independently.
• Demonstrates a desire to learn in the workplace and support growth within the lab.

• Conduct deep and thorough review of subject literature.
• Import datasets into a variety of software applications including R, SAS, and python, perform data cleaning.
• Develop machine learning algorithms, natural language processing tools, and end user tools.
• Develop and interpret MCMC models; develop meta-models.
• Analyze epidemiologic and administrative data using basic and advanced statistical methodologies; including regression modeling, survival analysis, causal inference, and propensity score matching; interpret results for investigators and prepare reports.
• Interpret model results to draw conclusions about intervention sustainability and cost-effectiveness.
• Write and edit manuscripts at various stages of development.