Senior Scientist, AI-Driven Anesthesiology Research

Washington University in St. Louis; St. Louis (MO); In loco; USD 63.000 - 115.000; Tempo pieno

Vantaggi offerti da questo lavoro

Health insurance

Transit benefit (Metro U-Pass)

Tuition assistance

Vacation & holidays

Descrizione del lavoro

Washington University in St. Louis presents a Senior Scientist opportunity in the Gulur Lab within WashU Medicine's Anesthesiology department.

The role focuses on designing and analyzing interdisciplinary studies using large clinical data, with emphasis on rigorous quantitative and computational methods across teams. Candidates should have a PhD or terminal degree and strong experience in study design, machine learning, and data integration.

Competenze

• PhD or terminal degree required; combination with experience may substitute for minimum education.
• Postdoctoral experience (3 years) noted as relevant.
• Strong quantitative and analytical skills with proficiency in R, Python, SAS, or SQL.
• Experience with large clinical or longitudinal datasets and data harmonization.
• Excellent written and verbal communication; ability to work in multidisciplinary teams.

Mansioni

• Lead defined research projects integrating large-scale clinical data with quantitative and computational methods.
• Develop studies from literature review through design, analysis, interpretation and dissemination.
• Collaborate with PI and collaborators to refine questions and new lines of investigation.
• Apply rigorous methods to complex clinical data using R, Python, SAS, SQL with documented workflows.
• Lead manuscripts, presentations, abstracts and grant applications.

Conoscenze

Quantitative analysis

Cross-disciplinary collaboration

Statistical methods

Written communication

Python

R

SQL

Machine learning

Formazione

PhD or Terminal Degree

Descrizione del lavoro

Washington University in St. Louis presents a Senior Scientist opportunity in the Gulur Lab within WashU Medicine's Anesthesiology department.

The role focuses on designing and analyzing interdisciplinary studies using large clinical data, with emphasis on rigorous quantitative and computational methods across teams. Candidates should have a PhD or terminal degree and strong experience in study design, machine learning, and data integration.