The Department of Cardiothoracic Surgery at Stanford University is conducting a search for a full-time Biostatistician to support clinical research activities of the Departments Faculty. This Faculty Statistician will work with Department Faculty on a number of initiatives that are in need of statistical support and leadership.
The candidate will:
- Lead the statistical analysis for a variety of studies.
Clinical efforts will include maintenance, manipulation, and analysis of clinical research datasets that will include both single-institution in-house patient populations, cohorts of patients assembled through multi-institution collaboration, and large-scale administrative and registry databases.
Supervise the conduct of the Cardiovascular Surgery clinical research database, including integrity checks and developing guidelines and rules for database error identification.
Examples of the large-scale databases that will be utilized include but are not limited to the Surveillance, Epidemiology, and End Results (SEER) program, the SEER-Medicare linked database, the Nationwide Inpatient Sample (NIS), the National Cancer Database (NCDB), the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP), and CMS MEDPAR.
Utilize conventional statistical methods including logistic regression analysis, proportional and non-proportional hazard modeling, propensity score analysis, and actual (or observed cumulative frequency) survival analyses to supplement the typical non-parametric actuarial methods for the evaluation of:
Short-term perioperative outcomes of morbidity and mortality following cardiovascular and thoracic surgical treatment, and identification of important factors related to these outcomes.
Long-term survival after treatment of cardiovascular and thoracic surgical diseases.
Incorporate novel statistical methods and cost analysis into the above studies as indicated, including via interfacing and collaboration with other statistical and modeling experts both within Stanford University and at external institutions.
Long-term survival and freedom from adverse events after treatment of cardiovascular and thoracic surgical diseases.
Develop and apply novel biostatistical methods to clinical investigations. This includes: 1.) Parametric modeling to decompose multiple time-varying hazards using a multiphase hazard model in the time domain, incorporating the effects of competing risks; 2.) Computer-intensive machine learning (or bagging) methods with bootstrap aggregation; random survival forest (RSF) analysis (nonparametric statistical ensemble method that utilizes all variable data without advance knowledge of the relationship [linear, nonlinear] of a variable over time or whether interactions exist); 3.) Nelsons cumulative event function to obtain nonparametric estimates; and, 4.) Multiple imputation using a Markov Chain Monte Carlo technique to impute missing values (SAS PROC MI).
Take a major role in applications for external funding, through support in developing, writing, and reviewing the statistical components of grants.
Participate in strategy sessions for designing and implementing studies, including proposals for analysis of external databases such as those maintained by the Society of Thoracic Surgeons for adult cardiac surgery patients, congenital cardiac surgery patients, and general thoracic surgery patients.
Upon completion of analyses, actively participate and collaborate with the cardiothoracic surgical faculty in preparation of both presentations at major thoracic surgical meetings and publications in major clinical and scientific journals based on the results.
A Masters or PhD degree in statistics, biostatistics, epidemiology, or a related field.
Three years or more of productive experience as a collaborating statistician on a variety of clinical study - designs, preferably in the cardiovascular realm, with previous publications in the field.
Knowledge and experience in SAS/SPSS/R/STATA or equivalent software/programming environments.
Knowledge of acquiring and maintaining publically available databases.
Highly self-motivated individual, enthusiastic about scientific discovery and able to collaborate closely and effectively with other members of a research team.
Dedication to teaching of clinical residents and fellows and the laboratory post-doctoral research fellows.
Excellent communication skills (verbal, written, and presentation).
Professional knowledge of biomedical research and new biostatistical methods
Located between San Francisco and San Jose in the heart of Silicon Valley, Stanford University is recognized as one of the world's leading research and teaching institutions. Leland and Jane Stanford founded the University to "promote the public welfare by exercising an influence on behalf of humanity and civilization." Stanford opened its doors in 1891, and more than a century later, it remains d...edicated to finding solutions to the great challenges of the day and to preparing students for leadership in a complex world. The University's thriving diverse community is comprised of nearly 7000 undergraduate students, 9000 graduate students, 2000 faculty members, 1900 postdoctoral scholars, and over 11,000 academic and administrative staff in seven schools including several interdisciplinary research centers and institutes. The campus spreads over 8000 contiguous acres and nearly all undergraduates live on campus. Stanford offers bachelor's and master's degrees in addition to doctoral degrees (PhD, MD, DMA and JD) plus a number of professional and continuing education programs and certifications. More at http://facts.stanford.edu and http://www.stanford.edu.
Stanford University is an equal opportunity employer and is committed to increasing the diversity of its faculty. It welcomes nominations of and applications from women, members of minority groups, protected veterans and individuals with disabilities, as well as from others who would bring additional dimensions to the university’s research, teaching and clinical missions.