Senior Scientist - Anesthesiology

Location: St. Louis

Location SAINT LOUIS, MO 63110

Scheduled Hours
40

Position Summary The Gulur Lab in the Department of Anesthesiology at WashU Medicine studies why patients respond differently to pain experiences and how we can alter their trajectory. We are seeking a Senior Scientist with strong expertise in study design, quantitative methods, and computational science who is excited to work across disciplines and help shape this research.

Collaborates on designing, conducting and reporting of research projects.

Job Description Primary

Duties & Responsibilities:

Lead defined research projects within the laboratory's broader scientific program, integrating large-scale clinical and longitudinal data with rigorous quantitative and computational approaches.

Develop and execute studies from literature review and hypothesis development through study design, protocol development, analysis, interpretation, and dissemination.

Work closely with the Principal Investigator and collaborators to refine research questions and develop new lines of investigation.

Apply rigorous and reproducible methods to complex clinical data using R, Python, SAS, SQL, or related tools, with well-documented code and workflows.

Apply longitudinal analysis, causal inference, machine learning, and AI-enabled approaches when appropriate to the scientific question.

Leverage large clinical studies, electronic health records, administrative or claims data, registries, and other large-scale datasets.

Collaborate with clinicians, epidemiologists, biostatisticians, informaticians, data scientists, data providers, and investigators across disciplines.

Coordinate data acquisition, harmonization, analysis, interpretation, and communication across research projects.

Lead and contribute to manuscripts, scientific presentations, abstracts, and grant applications.

Provide scientific and methodological guidance to junior analysts, research staff, students, and trainees.

Maintain high standards of scientific rigor, reproducibility, research integrity, and responsible conduct of research.

Maintain appropriate research records and comply with institutional data, privacy, security, and regulatory requirements.

Working Conditions:

Works in a laboratory environment with potential exposure to biological, chemical and radioactive hazards.

Must be physically able to wear protective equipment and to provide standard care to research animals.

The above statements are intended to describe the general nature and level of work performed by people assigned to this classification. They are not intended to be construed as an exhaustive list of all job duties performed by the personnel so classified. Management reserves the right to revise or amend duties at any time.

Required Qualifications

Education:

Phd Or Terminal Degree Or Combination Of Education And Experience May Substitute For

Minimum Education .

Certifications /Professional Licenses :

No specific certification/professional license is required for this position.

Work Experience:

Postdoctoral (3 Years)

Skills:

Not Applicable Driver's License:

A driver's license is not required for this position.

More About This Job

Preferred Qualifications:

PhD, MD, or equivalent doctoral degree in epidemiology, biostatistics, statistics, data science, biomedical informatics, quantitative health sciences, computer science, engineering, or a related discipline.

Demonstrated experience in quantitative clinical, epidemiologic, health services, or data science research.

Experience carrying research questions from study design through analysis, interpretation, and dissemination.

Experience working with large or complex datasets and contributing to scientific publications or presentations.

Strong quantitative and analytical skills and proficiency in one or more of R, Python, SAS, or SQL.Strong understanding of study design and statistical methods, with a commitment to reproducible research.

Excellent written and verbal communication skills and ability to work effectively in multidisciplinary teams.

Experience with large clinical studies, electronic health record data, claims data, registries, or longitudinal datasets.

Experience with longitudinal methods, causal inference, pharmacoepidemiology, comparative effectiveness research, predictive modeling, machine learning, or related approaches.

Experience applying machine learning or AI methods to biomedical or clinical research questions.

Experience with data harmonization across multiple data sources.

Experience leading multidisciplinary research projects,…