Staff Associate I

Description

SUMMARY: The position entails working as a team member of a health services research group in data science projects. One goal will be to aid appraisal of current literature for parameter inputs, epidemiological and biostatistical analysis, and post-processing analyses for computer disease simulation modeling. The focus of these mathematical models is to simulate masses that can represent benign or cancerous lesions, using a state-transition model (also known as Markov model) and Monte Carlo simulations. The assistant research scientist will also have a large role in manuscript writing, and thus experience with scientific writing is key. Other roles include dataset preparation and analysis of large registries and other observational datasets, literature searches for model inputs for incidence and mortality data, and preparation of presentations for meetings with collaborators and for national conferences. This position will require comprehension of epidemiologic and disease-related terminology, as well as familiarity with biostatistics and data visualization.

DUTIES AND RESPONSIBILITIES:

1. Conduct literature searches, post-processing and data visualization for mathematical disease models as described in the job summary.
2. Create manuscripts and presentation materials including graphics, charts, and figures.
3. Regularly meet with team and communicate the status of the project for trouble shooting.

4.    Aid dataset preparation and statistical analysis.

Qualifications

SUMMARY: The position entails working as a team member of a health services research group in data science projects. One goal will be to aid appraisal of current literature for parameter inputs, epidemiological and biostatistical analysis, and post-processing analyses for computer disease simulation modeling. The focus of these mathematical models is to simulate masses that can represent benign or cancerous lesions, using a state-transition model (also known as Markov model) and Monte Carlo simulations. The assistant research scientist will also have a large role in manuscript writing, and thus experience with scientific writing is key. Other roles include dataset preparation and analysis of large registries and other observational datasets, literature searches for model inputs for incidence and mortality data, and preparation of presentations for meetings with collaborators and for national conferences. This position will require comprehension of epidemiologic and disease-related terminology, as well as familiarity with biostatistics and data visualization.

DUTIES AND RESPONSIBILITIES:

1. Conduct literature searches, post-processing and data visualization for mathematical disease models as described in the job summary.
2. Create manuscripts and presentation materials including graphics, charts, and figures.
3. Regularly meet with team and communicate the status of the project for trouble shooting.

4.    Aid dataset preparation and statistical analysis.

MINIMUM JOB QUALIFICATIONS:

MS or MPH degree in a related discipline and at least 0-1 year of experience or equivalent combination of education and experience.

KNOWLEDGE, SKILLS, AND ABILITIES REQUIRED:

• Ability to communicate scientific concepts in manuscripts and oral presentation
• Ability to appraise literature using standard medical databases (e.g. pubmed/medline, Embase) and standard methods of systematic review
• Knowledge of statistics (at a minimum, multivariable regression, ideally generalized linear models, probability theory, and time-to-event analysis) and epidemiology, proven by successful completion of related coursework or research experience
• Some experience with programming in Python, R

DISTINGUISHING CHARACTERISTICS:

Strong candidates for this position will have: 1) experience with scientific writing; 2) strong understanding of basic statistical analysis and ability to use standard statistical packages; 3) familiarity with programming; 4) strong organizational skills

Equal Employment Opportunity Statement

Columbia University is an Equal Opportunity Employer / Disability / Veteran

Pay Transparency Disclosure

The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to departmental budgets, qualifications, experience, education, licenses, specialty, and training.  The above hiring range represents the University’s good faith and reasonable estimate of the range of possible compensation at the time of posting.