Post-Doctoral Research Associate Opportunity in the Madsen Lab
Setting: Dr. Madsen’s lab is housed within the Department of Emergency Medicine at the Larner College of Medicine at the University of Vermont. The lab is affiliated with the Vermont Center for Cardiovascular and Brain Health (VCCBH,
https://www.med.uvm.edu/heartbrainhealth). Dr. Madsen’s lab is funded by NIH/NHLBI, NIGMS, NINDS, the American Heart Association, and the AHRQ. We work to advance knowledge of both the epidemiology
and mechanisms of sex differences in stroke, brain health, and cardiometabolic disease through the lens of preventing and treating disease in women and improving women’s health at the population level.
Details: We are seeking to hire a post-doctoral researcher with interest in molecular epidemiology, women’s health, the science of sex and gender differences, and/or the use of epidemiologic and multi-omics data. In this role, the research
associate will receive training in and participate in work investigating sex differences in the epidemiology of cardiometabolic disease and stroke as well as mechanisms of disease and cardiovascular disease risk prediction. Under the general supervision
of the Principal Investigator and other team members, and within established policies and procedures, the researcher will perform scientific investigative research in the areas described above.
Educational Requirements:
Candidates must have a doctoral degree (PhD) in either biostatistics or epidemiology or equivalent training.
Experience/ Skills Required:
- Software/ Statistical Coding: Candidates must have proficiency using Microsoft Office, Microsoft Excel, R/ R Studio, SAS, and/or Python
- Strong quantitative skills with preference for candidates with ability to work with high dimensional data
- Excellent verbal and written communication skills including preparation and revision of scientific manuscripts
- Ability to work well on a team of investigators (with Principal Investigator, Co-Investigators, Head Biostatistician, doctoral students)
- Ability to design and create tables and figures for effective presentation of data
- Ability to supervise students and doctoral students
Training/ Learning Objectives:
Over the course of the post-doctoral experience the associate will:
- Learn to use of multi-dimensional data to investigate disease mechanism and risk
- Gain a foundation in sex and gender science along with skills to answer key questions about sex and gender differences using quantitative data and advanced statistical methodology
- Data analysis tasks will include: harmonization of data, data cleaning and analysis of patterns of missing data, time to event analyses, instrumental variable analyses, missing data imputation, network/ pathway analysis, and risk prediction/
modelling among other methods.
Description of Role/ Responsibilities, in conjunction with training objectives above:
- Assisting the PI in tasks such as obtaining, cleaning, harmonizing, and managing data
- Drafting study documents including paper proposals, revisions to paper proposals, manuscript drafts and critical revisions to manuscripts
- Coding and statistical analysis (a range of basic analytic methodologies to advanced casual inference statistical methods
- Creating tables and figures for presentation and publication
- For those who prefer hybrid or remote work, this will be considered on a case-by-case basis.
- Supervision of students (undergraduate, medical, and doctoral candidates)
Other information:
- Post-doctoral associates in Dr. Madsen's lab will receive direct mentorship from Dr. Madsen, lab PI and internationally known researcher in sex differences in stroke epidemiology and mechanism.
- Associates will have the opportunity to travel and network at key national meetings throughout their postdoc training.
- Associates will have the opportunity to connect with other scientists at UVM including faculty members in the Vermont Center for Cardiovascular and Brain Health (VCCBH, https://www.med.uvm.edu/heartbrainhealth)
Contact Information: Tracy.Madsen@uvm.edu
Location: University of Vermont, Burlington, VT; Remote/Hybrid work is a possibility, will be evaluated on a case-by-case basis.
Work Type: Full-Time