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Computational Researcher Jobs (NOW HIRING)

As a world-renowned medical and research center, we strive to provide the best possible care ... The Computational Scientist - BioHPC will work on the daily operations of the HPC system, provide ...

This role will drive researcher productivity by leading cross-functional collaborations, developing ... The ideal candidate holds a PhD in computational biology, bioinformatics, or a related field, with ...

This role will drive researcher productivity by leading cross-functional collaborations, developing ... The ideal candidate holds a PhD in computational biology, bioinformatics, or a related field, with ...

Stay current with advances in computational biology, machine learning, and scalable infrastructure, applying them to ongoing research challenges. * Communicate findings clearly through reports ...

Computational Neuroscientist

San Francisco, CA ยท On-site

$140K - $180K/yr

Computational Neuroscientist Alljoined is creating a future where humans are fully understood and ... We apply deep learning research to large scale EEG datasets to decode multimedia input, eventually ...

Develop and evaluate cutting-edge computational methodologies integrating multi-omic datasets to ... Track record of individual innovation, with published research or shipped work influencing pharma ...

Stay current with advances in computational biology, machine learning, and scalable infrastructure, applying them to ongoing research challenges. * Communicate findings clearly through reports ...

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Computational Researcher information

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$30K

$113.1K

$164.5K

How much do computational researcher jobs pay per year?

As of Jun 4, 2026, the average yearly pay for computational researcher in the United States is $113,102.00, according to ZipRecruiter salary data. Most workers in this role earn between $67,000.00 and $154,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Computational Researcher, and why are they important?

To thrive as a Computational Researcher, you need a strong background in mathematics, computer science, and domain-specific knowledge, typically supported by an advanced degree (MS or PhD) in a relevant field. Proficiency with programming languages like Python, R, or C++, as well as experience with high-performance computing, data analysis tools, and relevant simulation software, is often required. Critical thinking, problem-solving, and effective collaboration are essential soft skills that enable innovation and teamwork. These skills and qualifications are crucial for designing rigorous computational experiments, analyzing complex data, and contributing to impactful scientific advancements.

What are some typical challenges a Computational Researcher faces when collaborating with multidisciplinary teams?

Computational Researchers often work alongside scientists, engineers, and domain experts from various fields. One common challenge is translating complex computational models or results into accessible insights for collaborators who may not have a technical background. Balancing the differing project priorities and timelines of team members can also be demanding. However, effective communication and a collaborative mindset are key to ensuring successful, productive outcomes in these multidisciplinary environments.

What is a computational researcher?

A computational researcher is a professional who uses computer-based models, simulations, and algorithms to conduct scientific investigations and solve complex problems in various fields such as physics, biology, engineering, and social sciences. They leverage programming, mathematical modeling, and high-performance computing to analyze large datasets and generate insights that would be difficult or impossible to obtain through traditional experimental methods alone. Computational researchers often collaborate with domain experts to develop innovative solutions and advance scientific knowledge.

What job makes $10,000 a month without a degree?

A computational researcher typically requires advanced education, but some related roles like freelance data analysts, software developers, or digital marketers can earn $10,000 or more monthly through skills, experience, and freelance work. Success in these fields often depends on proficiency with programming, data analysis tools, or marketing platforms, and building a strong portfolio or client base is essential.

What is the difference between Computational Researcher vs Data Scientist?

AspectComputational ResearcherData Scientist
Required CredentialsAdvanced degrees in computer science, mathematics, or related fieldsDegree in statistics, computer science, or related fields; certifications like SAS or Python
Work EnvironmentResearch labs, academic institutions, industry R&D teamsBusiness environments, tech companies, consulting firms
Industry UsageAcademic research, scientific computing, R&D projectsBusiness analytics, product development, marketing insights
Common Search/ComparisonOften compared for research focus and technical skillsCompared for data analysis and business application skills

Computational Researchers primarily focus on developing new algorithms and conducting scientific research using computational methods, often within academic or R&D settings. Data Scientists analyze and interpret large datasets to inform business decisions. While both roles require strong technical skills and programming knowledge, their work environments and end goals differ significantly.

More about Computational Researcher jobs
Infographic showing various Computational Researcher job openings in the United States as of May 2026, with employment types broken down into 95% Full Time, 4% Part Time, and 1% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $113,102 per year, or $54.4 per hour.

Computational Research Associate

Neptune Bio

New York, NY โ€ข On-site

Full-time

Posted 3 days ago


Job description

Position Summary
We are seeking a Computational Research Associate to support our data analysis and infrastructure efforts across functional genomics and single-cell perturbation experiments. The ideal candidate has hands-on experience working with large biological datasets, enjoys building efficient and reproducible analysis workflows, and thrives in a collaborative, fast-paced startup environment.
You will play a central role in processing, analyzing, and organizing single-cell and perturb-seq data, maintaining and improving computational pipelines, and supporting the broader team with high-quality data outputs and infrastructure.
Key Responsibilities
  • Process and analyze large-scale single-cell and perturb-seq datasets using established computational pipelines.
  • Develop, document, and maintain reproducible analysis workflows and data processing infrastructure.
  • Support data management and organization across multiple internal and external datasets.
  • Collaborate closely with experimental and computational scientists to translate raw data into interpretable biological results.
  • Implement and optimize pipelines in cloud environments (e.g., AWS, GCP) for scalable data processing.
  • Maintain codebases, perform quality control on data outputs, and ensure reproducibility and traceability of analyses.
  • Generate clear reports, visualizations, and summaries to communicate results across teams.

Qualification and Education Requirements
You must have:
  • B.S. or M.S. in Bioinformatics, Computational Biology, Computer Science, or a related quantitative field.
  • 2+ years of experience working with biological or single-cell datasets.
  • Proficiency in Python and/or R for data analysis and visualization.
  • Familiarity with standard genomics tools and file formats (FASTQ, BAM, HDF5, AnnData, etc.).
  • Experience using and maintaining analysis pipelines in a Unix/Linux environment.
  • Experience working with cloud compute platforms (AWS, GCP, or similar).
  • Strong organizational skills, attention to detail, and commitment to clean, reproducible code.

Additional preferred experience includes:
  • Experience analyzing single-cell RNA-seq or perturb-seq datasets.
  • Familiarity with workflow management systems (Nextflow, Snakemake, or similar).
  • Experience with containerization tools such as Docker.
  • Exposure to data engineering concepts (e.g., databases, versioned data storage, data pipelines).
  • Understanding of basic statistical methods for genomics data analysis.