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Entry Level Remote Computational Biologist Jobs (NOW HIRING)

This opportunity can be remote. Duties and responsibilities: β€’ Support Oncology drug development ... Computational Biology, Genomics, Biostatistics, Bioinformatics and Biological Sciences) Salary:

Approval of remote and hybrid work is not guaranteed regardless of work location.For additional ... The laboratory employs integrative genomic and computational approaches in cattle and mouse models ...

AI Biologist - Function

San Francisco, CA Β· On-site +1

$120K - $180K/yr

Your hands-on expertise in functional biology assays and computational modeling will define how we ... Remote (globally), hybrid, or onsite in SF (onsite preferred) * Work authorization: OPT visa ...

Approval of remote and hybrid work is not guaranteed regardless of work location.For additional ... POSITION SPECIFICS Postdoctoral Scholar (Computational Biology) The National Synthesis Center for ...

Approval of remote and hybrid work is not guaranteed regardless of work location.For additional ... The focus of this search is on candidates with expertise in areas such as computational biology ...

Approval of remote and hybrid work is not guaranteed regardless of work location.For additional ... Contribute to research activities involving computational biology, bioinformatics, biological data ...

... biological datasets * Startup or early-stage company experience * Interest in translational medicine, toxicology, or computational drug development Location Hybrid and remote-friendly depending on ...

... biological datasets * Startup or early-stage company experience * Interest in translational medicine, toxicology, or computational drug development Location Hybrid and remote-friendly depending on ...

Approval of remote and hybrid work is not guaranteed regardless of work location.For additional ... cellular biology, and quantitative physical sciences. The Center provides leadership in the ...

Approval of remote and hybrid work is not guaranteed regardless of work location.For additional ... Current Penn State graduate student with demonstrated expertise in computational biology ...

Natera is hiring a Machine Learning Scientist to join our AI and computational biology team. This ... Remote USA $124,800-$171,600 USD OUR OPPORTUNITY Nateraβ„’ is a global leader in cell-free DNA ...

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Entry Level Remote Computational Biologist information

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How much do entry level remote computational biologist jobs pay per year?

As of Sep 12, 2026, the average yearly pay for entry level remote computational biologist in the United States is $93,988.00, according to ZipRecruiter salary data. Most workers in this role earn between $70,500.00 and $117,000.00 per year, depending on experience, location, and employer.
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Infographic showing various Entry Level Remote Computational Biologist job openings in the United States as of September 2026, with employment types broken down into 5% Internship, 66% Full Time, 28% Part Time, and 1% Contract. Highlights an 67% Physical, 2% Hybrid, and 31% Remote job distribution, with an average salary of $93,988 per year, or $45.2 per hour.

Junior Computational Biologist (Remote)

South San Francisco, CA β€’ On-site, Remote

Astrix Inc
Recruiting and Staffing ServicesΒ β€’Β 1 - 5K employees

$30 - $34/hr

Full-time

This job post hasΒ expired 3 days ago.Β Applications are no longer accepted.


Job description

Pay Rate Low: 30 | Pay Rate High: 34
A leading biotechnology research organization is seeking a Junior Computational Biologist to support efforts in refining how cellular states are quantified and validated!
Title: Jr. Computational Biologist (Remote Contract)
Location: Remote (Must be available during PST business hours)
Compensation: $30-34/hour + benefits
Contract Duration: 6-12+ months
Job Duties:
This project will focus on benchmarking functional scoring methodologies and improving interpretability of high-dimensional transcriptomic datasets.
The selected candidate will contribute to distinguishing true biological signal from technical variation in large-scale single-cell atlases, directly enhancing the reliability of automated cell-state classification frameworks.
Start Date: July 1, 2026
  • Duration: Through December 18, 2026
  • Commitment: Full-time (100%)
  • Ideal Candidate: Upcoming June 2026 PhD graduate or recent PhD graduate
  • Location: Onsite in South San Francisco, CA preferred; remote within the U.S. considered (must work PST hours)
  • Visa Sponsorship: Not availabl

Key Responsibilities
  • Systematically evaluate and benchmark computational approaches for quantifying phenotype activation across single-cell transcriptomic datasets.
  • Establish rigorous statistical baselines and negative-control frameworks to improve the robustness of automated cell-state classification methods.
  • Develop or refine computational methods to address limitations in current approaches.
  • Design strategies to distinguish genuine biological signatures from stochastic or technical noise.
  • Present findings in internal scientific reviews and contribute to potential conference abstracts or peer-reviewed publications.

Required Qualifications
  • Extensive hands-on experience in single-cell data analysis using Scanpy, AnnData, and Pandas.
  • Strong proficiency implementing statistical and machine learning models using scikit-learn and SciPy.
  • Demonstrated commitment to reproducible research practices and well-organized code.
  • Ability to clearly communicate complex computational concepts to interdisciplinary scientific teams.
  • Master's degree with ongoing PhD pursuit, or recent PhD graduate, in Computational Biology, Computer Science, Machine Learning, or related quantitative discipline.
  • Interest in drug discovery and comfort working in dynamic, research-driven environments.

Preferred Qualifications
  • Background knowledge in cell biology and/or immunology.
  • Experience with hypothesis testing, noise modeling, and benchmarking computational tools.
  • Familiarity with Explainable AI (XAI) approaches or large-scale biological datasets.
  • Demonstrated ability to build or extend novel bioinformatics pipelines.
    INDBH
    #LI-MG1