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Remote Biological Science Jobs in California (NOW HIRING)

Valiant

Wildlife Biologist

Ridgecrest, CA · Remote

Conduct pre-construction biological surveys and provide environmental compliance monitoring for ... Install and maintain remote cameras, acoustic monitoring equipment, and other wildlife monitoring ...

Learner Education

Online Science Tutor

Fresno, CA · Remote

$25/hr

Remote Hours: Set Your Own Schedule Pay: $25.00/hr About Learner Education Learner Education is on ... Subjects may include Biology, Chemistry, Physics, Environmental Science, and related areas. Tutors ...

Learner Education

Online Science Tutor

Fresno, CA · On-site +1

$25/hr

Remote Hours: Set Your Own Schedule Pay: $25.00/hr About Learner Education Learner Education is on ... Subjects may include Biology, Chemistry, Physics, Environmental Science, and related areas. Tutors ...

Osv_edf

Senior Scientist, Oceans Science

San Francisco, CA · On-site +1

$107K - $147K/yr

Location Remote US Home, Austin, Boulder, Boston, New York, San Francisco, Washington DC. Duration ... A PhD in ocean science, biological oceanography, biogeochemistry, marine ecology, or other related ...

Tempus

Bioinformatics Scientist

Redwood City, CA · On-site +1

$115K - $175K/yr

Computational skills using Python and/or R, including experience with data science and biological ... Additionally, for remote roles open to individuals in unincorporated Los Angeles - including remote ...

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Remote Biological Science information

What careers can you do with remote biological science?

Remote biological science careers include roles such as research scientist, bioinformatics analyst, scientific writer, and data analyst. These positions often require skills in laboratory techniques, data analysis, and familiarity with scientific software, and they can be performed from home with proper equipment and internet access.

What jobs can I do with a degree in biological sciences?

A degree in biological sciences qualifies individuals for roles such as research scientist, laboratory technician, biotechnologist, environmental consultant, or healthcare professional. These jobs often require laboratory skills, knowledge of biological systems, and sometimes certifications or advanced degrees depending on the position.

What remote biological science jobs can I do with a biology degree?

Remote biological science jobs for biology degree holders include roles such as research scientist, bioinformatics analyst, laboratory technician, scientific writer, and data analyst. These positions often require skills in data analysis, laboratory techniques, and familiarity with scientific software or tools, and may involve working independently or collaborating virtually with teams.
What are the most commonly searched types of Biological Science jobs in California? The most popular types of Biological Science jobs in California are:
What are popular job titles related to Remote Biological Science jobs in California? For Remote Biological Science jobs in California, the most frequently searched job titles are:
What job categories do people searching Remote Biological Science jobs in California look for? The top searched job categories for Remote Biological Science jobs in California are:
What cities in California are hiring for Remote Biological Science jobs? Cities in California with the most Remote Biological Science job openings:
Remote Biological Science jobs near you

Junior Computational Biologist (Remote)

Astrix Inc

South San Francisco, CA • On-site, Remote

$30 - $34/hr

Full-time

Re-posted 25 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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