Senior Scientist – Data‑Driven Anesthesiology & AI

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

Vantaggi offerti da questo lavoro

Vacation days & holidays

Health insurance

Metro U-Pass

Retirement plan (403b)

Tuition assistance

Descrizione del lavoro

Washington University in St. Louis’s Gulur Lab in Anesthesiology seeks a Senior Scientist to advance study design, quantitative approaches, and computational science across disciplines. The role involves leading projects, coordinating data from diverse sources, and contributing to publications and grants.

The ideal candidate will have PhD-level training, strong programming skills (R, Python, SAS, SQL), and experience with large clinical datasets and reproducible research practices.

Competenze

• Education: PhD or terminal degree or equivalent.
• Demonstrated experience in quantitative clinical/epidemiologic or data science research.
• Experience leading multidisciplinary research projects and teams.

Mansioni

• Lead defined research projects integrating large-scale clinical and longitudinal data.
• Design, analyze, and report studies from design to dissemination.
• Collaborate with clinicians, epidemiologists, biostatisticians, informaticians and data scientists across disciplines.
• Apply rigorous methods to complex clinical data using R, Python, SAS, SQL with reproducible code.
• Use longitudinal, causal inference, and machine learning approaches as appropriate.
• Lead manuscripts, presentations, abstracts and grant applications.

Conoscenze

Study design

Quantitative methods

Computational science

Machine learning

Mentoring

Formazione

PhD or terminal degree

Strumenti

R

Python

SAS

SQL

Descrizione del lavoro

Washington University in St. Louis’s Gulur Lab in Anesthesiology seeks a Senior Scientist to advance study design, quantitative approaches, and computational science across disciplines. The role involves leading projects, coordinating data from diverse sources, and contributing to publications and grants.

The ideal candidate will have PhD-level training, strong programming skills (R, Python, SAS, SQL), and experience with large clinical datasets and reproducible research practices.