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Postdoc In Usa Jobs in Ashburn, VA (NOW HIRING)

Postdoc In Usa information

See Ashburn, VA salary details

$25.6K

$60.4K

$85.4K

How much do postdoc in usa jobs pay per year?

As of Aug 15, 2026, the average yearly pay for postdoc in usa in Ashburn, VA is $60,356.00, according to ZipRecruiter salary data. Most workers in this role earn between $50,100.00 and $68,000.00 per year, depending on experience, location, and employer.

What is the difference between Postdoc In Usa vs Research Scientist In Usa?

AspectPostdoc In UsaResearch Scientist In Usa
Required CredentialsPhD in relevant fieldMaster's or PhD, often with more industry experience
Work EnvironmentAcademic labs, universitiesIndustry labs, corporate R&D
Employer & Industry UsageUniversities, research institutionsPrivate companies, government agencies
Common Search & Comparison IntentAcademic research roles, postdoctoral opportunitiesIndustry research roles, career advancement

In summary, a Postdoc In Usa typically involves academic research with a PhD and focuses on advancing knowledge in a university or research institution. A Research Scientist In Usa often requires similar credentials but is more industry-oriented, working within corporate or government R&D settings for product development or applied research.

What are popular job titles related to Postdoc In Usa jobs in Ashburn, VA?

For Postdoc In Usa jobs in Ashburn, VA, the most frequently searched job titles are:

Postdoctoral Fellows - Computational Biology & Machine Learning

The Henry M. Jackson Foundation for the Advancement of Military Medicine

Bethesda, MD • On-site

$52K - $71K/yr

Full-time

Posted 4 days ago


Job description

Job Summary:
The Henry M. Jackson Foundation for the Advancement of Military Medicine is a nonprofit organization dedicated to advancing military medicine. They are seeking a Postdoctoral Fellow in Computational Biology & Machine Learning to lead innovative research projects and develop AI/ML tools for cancer genomics analysis.
Responsibilities:
• Lead Innovative research. Conceive and execute computational research projects, develop novel algorithms and analytical frameworks to interrogate large-scale, multidimensional omics datasets, and translate findings into clinically meaningful insights. Motivation to lead research projects under Principal Investigator’s supervision.
• Build Artificial Intelligence (AI)/Machine Learning (ML) tools. Design, implement, document, and publicly release AI/ML models - including deep learning approaches - for integrative analysis of cancer genomic data, contributing resources that advance the broader scientific community.
• Engineer scalable pipelines. Develop and maintain robust, reproducible computational pipelines for processing, integrating, and managing complex biomedical datasets across multiple data modalities.
• Drive scientific communication. Lead and contribute to the preparation of high-impact scientific manuscripts, grant and fellowship applications, and conference presentations; represent the lab at national and international scientific meetings.
• Collaborate across disciplines. Actively contribute to team meetings and foster a culture of scientific excellence within a diverse, interdisciplinary research environment.
Qualifications:
Required:
• A PhD in Bioinformatics, Computational Biology, Systems Biology, Quantitative Genomics, Biomedical Engineering, Machine Learning, Computer Science (with a computational biology focus), or a closely related field is required.
• Candidates at all stages of their postdoctoral career (0–5 years of postdoctoral experience) are encouraged to apply.
• Strong foundation in statistical and computational modeling and data analysis applied to genomics questions is required.
• Experience with Artificial Intelligence (AI)/Machine Learning (ML) (deep learning) methods applied to cancer genomics is considered a strong asset.
• Demonstrated experience developing or applying computational or statistical pipelines to molecular, biological, clinical, or multi-omics data.
• Proficiency in Python, R, and/or C/C++, with hands-on experience using scientific computing libraries (e.g., pandas, NumPy, SciPy, scikit-learn, Bioconductor).
• Demonstrated experience building or applying computational/statistical pipelines to molecular, clinical, or multi-omics datasets.
• Proficiency with reproducible workflow management systems such as Snakemake, Nextflow, or equivalent pipeline frameworks.
• Familiarity with cloud or high-performance computing (HPC) environments, such as Google Cloud, Amazon AWS, SLURM/SGE-based clusters, or equivalent infrastructure.
• Experience applying AI/ML and deep learning methods to cancer genomics problems - particularly single-cell omics, spatial omics, epigenomics, or liquid biopsy fragmentomics is highly valued.
• Prior work with large-scale biomedical datasets, including multi-omics, single-cell, spatial, clinical genomics, or treatment-response data is highly valued.
• A track record of peer-reviewed publications commensurate with career stage in computational biology, bioinformatics, biomedical data science, or related fields is highly valued.
• Proven ability to collaborate effectively within large, interdisciplinary teams.
• Strong organizational skills with the ability to manage multiple priorities and meet deadlines in a fast-paced research environment.
• Excellent written and verbal communication skills in English, including demonstrated scientific writing ability.
• Ability to obtain and maintain a T1/Public Trust background check.
• Ability to stand or sit at a computer for prolonged periods.
Company:
The Henry M. Founded in 1983, the company is headquartered in Bethesda, USA, with a team of 1001-5000 employees. The company is currently Late Stage.