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Amazon Bioinformatics Jobs in Washington (NOW HIRING)

Amazon Bioinformatics information

What is an Amazon bioinformatics?

An Amazon Bioinformatics job involves applying computational and statistical techniques to analyze biological data, often in support of Amazon's healthcare, life sciences, or agritech initiatives. Professionals in this role work with large datasets, develop algorithms, and use machine learning to derive insights from genomic, proteomic, or other biological information. They collaborate with scientists, engineers, and product teams to develop innovative solutions for personalized medicine, drug discovery, or agricultural optimization.

What does an Amazon bioinformatics do?

Bioinformatics professionals at Amazon may work on projects ranging from designing and optimizing genomic data pipelines to analyzing large-scale biological datasets that support various company initiatives, such as supply chain improvements or healthcare applications. Daily tasks often include collaborating with data engineers and scientists, writing code to automate data processing, interpreting results, and presenting findings to stakeholders. There is a strong focus on teamwork, as you’ll frequently interact across departments to translate scientific insights into actionable business solutions. As part of a dynamic and tech-driven environment, you’ll also have opportunities to continuously learn new technologies and methodologies, which can lead to exciting career advancement possibilities.

What are the key skills and qualifications needed for an Amazon bioinformatics?

To thrive in an Amazon Bioinformatics role, you typically need a strong background in molecular biology, computational biology, and data analysis, often supported by a graduate degree in bioinformatics or a related field. Familiarity with programming languages such as Python or R, experience with bioinformatics software tools, and knowledge of cloud computing platforms like AWS are common requirements. Exceptional problem-solving abilities, effective communication, and the capacity to work collaboratively in diverse, cross-functional teams set top candidates apart. These skills and qualities are essential to efficiently analyze large-scale biological data, drive innovation, and support data-driven decisions in a fast-paced tech-enabled environment.

What jobs can I get with Amazon Bioinformatics?

With Amazon Bioinformatics, you can pursue roles such as bioinformatics scientist, data analyst, research scientist, or software engineer specializing in genomics and computational biology. These positions typically require skills in programming, data analysis, and knowledge of biological data, often utilizing tools like Python, R, and cloud computing platforms like AWS.
Infographic showing various Amazon Bioinformatics job openings in Washington as of August 2026, with employment types broken down into 57% Full Time, and 43% Part Time. Highlights an 48% In-person, and 52% Remote job distribution.

Postdoctoral Fellows - Computational Biology & Machine Learning

Bethesda, MD • On-site

The Henry M. Jackson Foundation for the Advancement of Military Medicine
Scientific Research and Development Services • 1 - 5K employees

$52K - $71K/yr

Full-time

Re-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.