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How much do genetic epidemiology jobs pay per year?

As of Jul 30, 2026, the average yearly pay for genetic epidemiology in the United States is $85,222.00, according to ZipRecruiter salary data. Most workers in this role earn between $64,000.00 and $101,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Genetic Epidemiology position, and why are they important?

To excel in Genetic Epidemiology, you need a solid background in genetics, epidemiology, biostatistics, and data analysis, often supported by an advanced degree in public health, genetics, or a related field. Familiarity with statistical software such as R, SAS, or STATA, and knowledge of genetic databases and bioinformatics tools, is highly valued. Strong analytical thinking, problem-solving abilities, and excellent communication skills help translate complex data into actionable insights and collaborate with multidisciplinary teams. These competencies are crucial for designing robust studies, interpreting genetic data, and advancing public health outcomes.

What are typical responsibilities for someone working in Genetic Epidemiology?

Professionals in Genetic Epidemiology design and conduct studies to investigate the genetic factors that influence the distribution and determinants of diseases in populations. This often involves analyzing large datasets, interpreting data to identify genetic risk factors, and collaborating with clinicians, laboratory scientists, and other researchers. Daily tasks may include data collection, statistical analysis, drafting research papers, and presenting findings to both scientific and non-scientific audiences. Teamwork and effective communication across disciplines are key aspects of this role, as is staying current with emerging research and technologies in the field.

What is a Genetic Epidemiology job?

A Genetic Epidemiology job involves studying how genetic factors influence health and disease patterns in populations. Professionals in this field analyze genetic data to identify hereditary risks, assess gene-environment interactions, and contribute to disease prevention efforts. They often work in research institutions, public health organizations, or pharmaceutical companies, using statistical and bioinformatics tools to interpret genetic contributions to health outcomes.

More about Genetic Epidemiology jobs
What cities are hiring for Genetic Epidemiology jobs? Cities with the most Genetic Epidemiology job openings:
What are the most commonly searched types of Genetic Epidemiology jobs? The most popular types of Genetic Epidemiology jobs are:
What states have the most Genetic Epidemiology jobs? States with the most job openings for Genetic Epidemiology jobs include:
What job categories do people searching Genetic Epidemiology jobs look for? The top searched job categories for Genetic Epidemiology jobs are:
Genetic Epidemiology jobs near you
Infographic showing various Genetic Epidemiology job openings in the United States as of July 2026, with employment types broken down into 1% Locum Tenens, 81% Full Time, 15% Part Time, 1% Temporary, 1% Contract, and 1% Summer. Highlights an 79% Physical, 4% Hybrid, and 17% Remote job distribution, with an average salary of $85,222 per year, or $41 per hour.

Postdoctoral Fellow - Genetic Epidemiology

University of Maryland, Baltimore

Baltimore, MD • On-site

$48K - $66K/yr

Full-time

Re-posted 23 days ago

University Of Maryland, Baltimore rating

7.7

Company rating: 7.7 out of 10

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Job description

Job Description
Postdoctoral Fellow - Genetic Epidemiology
Division of Endocrinology, Diabetes, and Nutrition University of Maryland School of Medicine Baltimore, Maryland
Position Description:
The Division of Endocrinology, Diabetes, and Nutrition (EDN) at the University of Maryland School of Medicine, Baltimore (UMB), is recruiting a computational Postdoctoral Fellow in the field of genetic epidemiology. This position offers an exciting opportunity to work with large epidemiological datasets on African populations, contributing to cutting-edge research aimed at disentangling the determinants and underlying mechanisms of cardiometabolic diseases in these populations. African ancestry populations are disproportionally affected by cardiometabolic diseases such as type 2 diabetes, hypertension, and obesity. The reasons for this disproportionate burden are poorly understood, but they are thought to result from a complex interplay between genetic and environmental factors. African-ancestry populations are severely unrepresented in research studies, particularly in genomics research, while insights from these types of studies are needed to better understand the underlying causes of cardiometabolic diseases in these populations and develop appropriate treatment and prevention efforts.
The Postdoctoral Fellow will work on study design, study implementation, data analysis, and drafting of manuscripts on projects focused on identifying genetic, epigenetic, metabolic, and lifestyle factors for cardiometabolic diseases in Africans living in Africa, African migrants living in the US and Europe, as well as African Americans. There will ample opportunity to present, publish, and kickstart a fruitful career in academia or industry.
The Division of Endocrinology, Diabetes, and Nutrition
( is located in the new Health Sciences Research Facility III building in Baltimore, which is equipped with state-of-the art laboratories and cutting-edge technology. Career development support and training opportunities will be available within the lab and through the Center for Advanced Research Training and Innovation
Qualifications
Qualifications:
Minimum qualifications:
Candidates should be close to obtaining a PhD, or have obtained a PhD within the past five years, in genetic epidemiology, statistical genetics, genomics, epidemiology/public health, computational biology, bioinformatics, or a related field. Applicants must have experience or interest in developing expertise on genomic, epidemiologic, and bioinformatic approaches to investigating the genetic architecture of complex traits.

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