Entry Level Computational Scientist Jobs
New grad computational scientist jobs welcome recent graduates and entry level candidates with zero to two years of experience, where a strong portfolio or internship work can matter more than a long resume. Most openings are on-site roles across Biotechnology & Pharmaceuticals, Science & Research, and Education, with employers like Broad Institute, Generate Biomedicines, and MESO SCALE DIAGNOSTICS hiring at this level now.
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Zymo Research is seeking a Bioinformatics Scientist to join the Epigenetics Technology team and lead computational development for epigenomics and molecular assay research. The scientist will curate datasets, discover and evaluate candidate methylation biomarkers, develop statistical models, and build reproducible analysis pipelines in close collaboration with experimental scientists.
This role combines epigenomics, statistical modeling, and software development. The scientist will guide computational strategy, define analytical performance criteria, and support targeted assay development, independent validation, and transfer into scalable research products.
Join us in making a meaningful impact!
- Own the computational roadmap for assigned research and assay development projects, defining deliverables, milestones, acceptance criteria, data needs, and technical risks. Coordinate priorities and dependencies with experimental scientists and support bioinformatics teams.
- Curate public and internal epigenomic datasets (methylation, hydroxymethylation). Document sample provenance, quality, relevant metadata, assay platform, genome build, and usage permissions; maintain versioned datasets with clear inclusion and quality criteria.
- Discover and prioritize candidate molecular markers and differentially methylated regions. Evaluate specificity, biological variability, common sequence variants, repetitive regions, assay compatibility, and stability across relevant sample and biological conditions.
- Develop and benchmark statistical models for molecular profiling and epigenetic biomarker analysis. Evaluate feature selection, model assumptions, uncertainty and performance supported by the available data.
- Contribute to other projects requiring relevant scientific and technical expertise.
Pipeline Development and Validation
- Build reproducible pipelines for methylation sequencing and relevant reference array datasets, covering quality control, alignment, methylation quantification, filtering, annotation, and reporting. Evaluate conversion efficiency, mapping ambiguity, duplicates, coverage, and batch effects using controls appropriate to each assay.
- Co-design targeted methylation panels with the assay team. Perform in silico assessment of primers, probes, and hybridization capture baits for sequence specificity, common variants, conversion-related sequence changes, and cross-hybridization; use empirical enrichment and coverage data to refine panel design.
- Benchmark analytical methods using reference standards, simulations, and independent sample sets. Separate model development, marker selection, and validation by biological source; assess bias, error, agreement, reproducibility, and robustness.
- Assess robustness to sequencing depth, missing data, DNA input, dataset selection, platform differences, batch effects, and relevant biological variation. Use validated harmonization approaches and prevent information leakage across development and validation datasets.
- Define quantitative reporting metrics, calibration approaches, quality thresholds, and validated reporting ranges. Document uncertainty, investigate unexpected results, and communicate analytical limitations.
- Implement automated quality checks, failure flags, versioned reports, and traceable software releases. Use code review, tests, workflow automation, and documented environments to support reproducibility and technical transfer; communicate model limitations clearly to scientific and product teams.
Additional Responsibilities
- Provide technical guidance and code review for collaborating scientists and junior bioinformatics staff. Maintain clear analysis documentation, contribute to publications and invention disclosures, and support product and customer-facing technical discussions as needed for relevant projects.
Education and Experience:
- Ph.D. in bioinformatics, computational biology, computer science, genomics, or a related discipline, with demonstrated independent ownership of substantial computational research or product development projects.
- Strong experience analyzing DNA (hydroxy)methylation or epigenomic data, including sequencing-based quantification, quality control, and biological interpretation.
- Experience with statistical modeling, biomarker discovery, or closely related quantitative methods, including rigorous study design, feature selection, and independent model validation.
Required Technical Skills
- Proficiency in Python and R, Linux or Unix, statistical analysis, and scientific visualization. Experience building maintainable analysis code with version control, automated tests, and documented workflows.
- Experience processing Illumina sequencing data, managing large genomic datasets, and developing scalable workflows using high-performance or cloud computing environments.
- Experience with epigenomic biomarker discovery, dataset curation, method benchmarking, or statistical model optimization.
- Strong communication skills and evidence of original scientific contributions through publications/posters, validated analytical methods, or deployed analysis tools (e.g. GitHub). Ability to explain uncertainty and analytical tradeoffs to multidisciplinary collaborators.
Preferred Qualifications
- Experience with targeted methylation sequencing, hybridization capture panel design, multiplex primer or probe design, or analysis of methylation-sensitive qPCR or digital PCR data.
- Experience analyzing DNA variants/SNPs using NGS data and appropriate quality control and validation methods.
- Experience comparing molecular assay results with independent measurements and assessing analytical agreement, bias, and reproducibility.
- Experience with cross-platform methylation analysis (Nanopore/PacBio), low-input assays, uncertainty estimation, workflow engines, or transfer of analytical methods into supported research products.
About Us:
Since its inception in 1994, Zymo Research has been proudly serving the scientific community by providing innovative, reliable, and high-quality research tools and products. Whether it's DNA, RNA, epigenetics, microbiomics, protein, or yeast-based research, our philosophy remains the same: To provide the highest quality products in the industry while ensuring they are both simple to use and reliable in their performance.
Compensation, Benefits, and Perks:
Zymo Research also offers competitive benefits and perks including:
- Medical, Dental, Vision, and Life Insurance Coverages
- EAP Sessions
- Vacation Time plus Company Holidays
- Paid Sick Leave
- Generous 401(K) with matching
- Employee Referral Bonus
- Complimentary fruit, snacks, and beverages
- Complimentary catered lunches on Thursdays
- Complimentary EV Charging Cell phone stipend
Equal Employment Opportunity Employer:
Location:
Disclaimer: At Zymo, we take the integrity of our hiring process seriously. Please be aware of fraudulent recruitment activities that may use our name to deceive job seekers. We will never ask for payment, sensitive personal information, or financial details during the recruitment process.
All legitimate communications will come from an official Zymo or TriNet Hiring email address. If you are contacted by anyone claiming to represent us using a free email service (e.g., Gmail, Yahoo, Hotmail) or asking for payment, please treat this as fraudulent and report it immediately to careers@zymoresearch.com
Zymo Research is seeking a Bioinformatics Scientist to join the Epigenetics Technology team and lead computational development for epigenomics and molecular assay research. The scientist will curate datasets, discover and evaluate candidate methylation biomarkers, develop statistical models, and build reproducible analysis pipelines in close collaboration with experimental scientists.
This role combines epigenomics, statistical modeling, and software development. The scientist will guide computational strategy, define analytical performance criteria, and support targeted assay development, independent validation, and transfer into scalable research products.
Join us in making a meaningful impact!
- Own the computational roadmap for assigned research and assay development projects, defining deliverables, milestones, acceptance criteria, data needs, and technical risks. Coordinate priorities and dependencies with experimental scientists and support bioinformatics teams.
- Curate public and internal epigenomic datasets (methylation, hydroxymethylation). Document sample provenance, quality, relevant metadata, assay platform, genome build, and usage permissions; maintain versioned datasets with clear inclusion and quality criteria.
- Discover and prioritize candidate molecular markers and differentially methylated regions. Evaluate specificity, biological variability, common sequence variants, repetitive regions, assay compatibility, and stability across relevant sample and biological conditions.
- Develop and benchmark statistical models for molecular profiling and epigenetic biomarker analysis. Evaluate feature selection, model assumptions, uncertainty and performance supported by the available data.
- Contribute to other projects requiring relevant scientific and technical expertise.
Pipeline Development and Validation
- Build reproducible pipelines for methylation sequencing and relevant reference array datasets, covering quality control, alignment, methylation quantification, filtering, annotation, and reporting. Evaluate conversion efficiency, mapping ambiguity, duplicates, coverage, and batch effects using controls appropriate to each assay.
- Co-design targeted methylation panels with the assay team. Perform in silico assessment of primers, probes, and hybridization capture baits for sequence specificity, common variants, conversion-related sequence changes, and cross-hybridization; use empirical enrichment and coverage data to refine panel design.
- Benchmark analytical methods using reference standards, simulations, and independent sample sets. Separate model development, marker selection, and validation by biological source; assess bias, error, agreement, reproducibility, and robustness.
- Assess robustness to sequencing depth, missing data, DNA input, dataset selection, platform differences, batch effects, and relevant biological variation. Use validated harmonization approaches and prevent information leakage across development and validation datasets.
- Define quantitative reporting metrics, calibration approaches, quality thresholds, and validated reporting ranges. Document uncertainty, investigate unexpected results, and communicate analytical limitations.
- Implement automated quality checks, failure flags, versioned reports, and traceable software releases. Use code review, tests, workflow automation, and documented environments to support reproducibility and technical transfer; communicate model limitations clearly to scientific and product teams.
Additional Responsibilities
- Provide technical guidance and code review for collaborating scientists and junior bioinformatics staff. Maintain clear analysis documentation, contribute to publications and invention disclosures, and support product and customer-facing technical discussions as needed for relevant projects.
Education and Experience:
- Ph.D. in bioinformatics, computational biology, computer science, genomics, or a related discipline, with demonstrated independent ownership of substantial computational research or product development projects.
- Strong experience analyzing DNA (hydroxy)methylation or epigenomic data, including sequencing-based quantification, quality control, and biological interpretation.
- Experience with statistical modeling, biomarker discovery, or closely related quantitative methods, including rigorous study design, feature selection, and independent model validation.
Required Technical Skills
- Proficiency in Python and R, Linux or Unix, statistical analysis, and scientific visualization. Experience building maintainable analysis code with version control, automated tests, and documented workflows.
- Experience processing Illumina sequencing data, managing large genomic datasets, and developing scalable workflows using high-performance or cloud computing environments.
- Experience with epigenomic biomarker discovery, dataset curation, method benchmarking, or statistical model optimization.
- Strong communication skills and evidence of original scientific contributions through publications/posters, validated analytical methods, or deployed analysis tools (e.g. GitHub). Ability to explain uncertainty and analytical tradeoffs to multidisciplinary collaborators.
Preferred Qualifications
- Experience with targeted methylation sequencing, hybridization capture panel design, multiplex primer or probe design, or analysis of methylation-sensitive qPCR or digital PCR data.
- Experience analyzing DNA variants/SNPs using NGS data and appropriate quality control and validation methods.
- Experience comparing molecular assay results with independent measurements and assessing analytical agreement, bias, and reproducibility.
- Experience with cross-platform methylation analysis (Nanopore/PacBio), low-input assays, uncertainty estimation, workflow engines, or transfer of analytical methods into supported research products.
About Us:
Since its inception in 1994, Zymo Research has been proudly serving the scientific community by providing innovative, reliable, and high-quality research tools and products. Whether it's DNA, RNA, epigenetics, microbiomics, protein, or yeast-based research, our philosophy remains the same: To provide the highest quality products in the industry while ensuring they are both simple to use and reliable in their performance.
Compensation, Benefits, and Perks:
Zymo Research also offers competitive benefits and perks including:
- Medical, Dental, Vision, and Life Insurance Coverages
- EAP Sessions
- Vacation Time plus Company Holidays
- Paid Sick Leave
- Generous 401(K) with matching
- Employee Referral Bonus
- Complimentary fruit, snacks, and beverages
- Complimentary catered lunches on Thursdays
- Complimentary EV Charging Cell phone stipend
Equal Employment Opportunity Employer:
Location:
Disclaimer: At Zymo, we take the integrity of our hiring process seriously. Please be aware of fraudulent recruitment activities that may use our name to deceive job seekers. We will never ask for payment, sensitive personal information, or financial details during the recruitment process.
All legitimate communications will come from an official Zymo or TriNet Hiring email address. If you are contacted by anyone claiming to represent us using a free email service (e.g., Gmail, Yahoo, Hotmail) or asking for payment, please treat this as fraudulent and report it immediately to careers@zymoresearch.com
See All 15 Entry Level Computational Scientist Jobs
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Entry Level Computational Scientist Jobs: Frequently Asked Questions
How do I get an entry level computational scientist job?
Entry level computational scientist roles reward candidates who can demonstrate practical skills through GitHub repositories, research projects, or internship experience. Employers at this level typically look for proficiency in Python, C++, or MATLAB, familiarity with numerical methods and simulation, and the ability to communicate technical results clearly. A capstone project or published code sample can substitute for years of professional experience when your resume is light.
Which companies hire entry level computational scientists?
Companies hiring entry level computational scientists right now include Broad Institute, Generate Biomedicines, and MESO SCALE DIAGNOSTICS, based on current listings on Migrate Mate as of November 2026. At this level, hiring tends to come from national laboratories, defense contractors, pharmaceutical research firms, and technology companies building simulation or modeling capabilities.
Are there remote entry level computational scientist jobs?
Yes, though on-site roles remain common for new graduates in this field. About 42% of entry level computational scientist openings are remote or hybrid as of November 2026, concentrated in software-heavy or data-focused roles where simulation work can be done independently. On-site positions tend to dominate in lab-based or hardware-adjacent environments.
Are these new grad computational scientist jobs?
Yes, this page includes new grad, recent graduate, and junior computational scientist roles. A new grad friendly posting typically welcomes zero to two years of experience, accepts internship or academic project work in place of professional tenure, and does not require prior industry employment. If the description mentions a thesis, coursework, or a portfolio, it is almost certainly open to new grads.
Which industries hire the most entry level computational scientists?
Entry level computational scientist roles concentrate in Biotechnology & Pharmaceuticals, Science & Research, and Education, based on current listings on Migrate Mate as of November 2026. These sectors drive hiring at this level because they depend heavily on simulation, modeling, and high-performance computing work that suits candidates with strong quantitative training but limited professional history.