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Remote Entry Level Computational Biology Jobs (NOW HIRING)

YO IT Consulting

Biology Expert - Remote

... with a remote team to enhance AI understanding and performance. Responsibilities : • Analyze ... computational biology or data analysis tools Company : Our Core mission is to develop, deploy, or ...

YO IT Consulting

Biology Expert - Remote

... with a remote team to enhance AI understanding and performance. Responsibilities : • Analyze ... computational biology or data analysis tools Company : Our Core mission is to develop, deploy, or ...

The Pennsylvania State University

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 ...

The Pennsylvania State University

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 ...

The Pennsylvania State University

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 ...

Freenome

Staff Machine Learning Scientist

Brisbane, CA · On-site +1

$199K - $283K/yr

... remote. What you'll do: * Independently pursue cutting edge research in AI applied to biological problems (including cancer research, genomics, computational biology, immunology, etc.). * Build new ...

The Pennsylvania State University

... remote work. Responsibilities: * Collaborate with NCEMS Working Groups to design and implement computational methods for integrating, analyzing, and visualizing complex molecular and cellular biology ...

Natera

Machine Learning Scientist, Multimodal AI

$124K - $171K/yr

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 Natera™ is a global leader in cell-free DNA ...

The Pennsylvania State University

Approval of remote and hybrid work is not guaranteed regardless of work location.For additional ... We are part of the Center for Medical Genomics and the Center for Computational Biology and ...

Absentia Labs

Member of the Technical Staff

Boston, MA · Remote

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

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All JobsRemote Entry Level Computational Biology Jobs

Remote Entry Level Computational Biology information

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

As of Jun 21, 2026, the average yearly pay for remote entry level computational biology 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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What cities are hiring for Remote Entry Level Computational Biology jobs? Cities with the most Remote Entry Level Computational Biology job openings:
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Remote Entry Level Computational Biology jobs near you
Infographic showing various Remote Entry Level Computational Biology job openings in the United States as of June 2026, with employment types broken down into 5% Internship, 58% Full Time, 21% Part Time, 5% Temporary, and 11% Contract. Highlights an 100% Remote job distribution, with an average salary of $93,988 per year, or $45.2 per hour.
Junior Computational Biologist (Remote)

Junior Computational Biologist (Remote)

Astrix Inc

South San Francisco, CA • On-site, Remote

$30 - $34/hr

Full-time

Posted 8 days ago

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

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