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Junior Bioinformatics Remote Jobs in California (NOW HIRING)

Partner closely with bioinformatics, statistical, and medical experts to document projects ... This is a remote friendly position for both US and Canada based candidates. * On-site desk-space is ...

New

Principal Software Engineer

South San Francisco, CA · Remote

$162K - $217K/yr

Remote optional Job Type: Full-time About the Role We're seeking a Principal Software Engineer to ... You've led an engineering team before and have mentored junior engineers. You're comfortable being ...

Junior Bioinformatics Remote information

What is a junior bioinformatics remote?

A Junior Bioinformatics Remote job involves analyzing biological data, such as DNA sequences or protein structures, using computational tools and software while working from a remote location. Responsibilities may include data processing, scripting, statistical analysis, and assisting senior bioinformaticians in research projects. Employers typically look for candidates with a background in bioinformatics, biology, computer science, or a related field, along with proficiency in programming languages like Python, R, or SQL. This role offers flexibility but requires strong communication and collaboration skills to work effectively with remote teams.

What are the key skills and qualifications needed to thrive in the junior bioinformatics remote position, and why are they important?

To thrive as a Junior Bioinformatics Remote, you need a solid understanding of biology, statistics, and programming languages such as Python or R, usually supported by a relevant degree. Familiarity with bioinformatics tools like BLAST, Bioconductor, and databases such as NCBI or Ensembl, as well as experience with version control systems like Git, is highly valued. Strong attention to detail, effective communication, and the ability to work independently in a distributed team environment are key soft skills. These abilities enable you to analyze complex biological data accurately and efficiently while collaborating across remote teams.

What are the typical projects or tasks a junior bioinformatics remote might work on?

As a Junior Bioinformatics Remote, typical tasks include processing and analyzing large biological datasets like genomics or transcriptomics data, maintaining and updating bioinformatics pipelines, and generating reports or visualizations to communicate findings. You may assist in troubleshooting data quality issues, support senior team members with ongoing research projects, and help integrate new data sources or software tools. Collaboration often occurs via virtual meetings and project management platforms, allowing you to contribute to multidisciplinary research from a remote setting. These varied responsibilities provide valuable hands-on experience and a clear pathway toward more senior roles in bioinformatics.

What are popular job titles related to Junior Bioinformatics Remote jobs in California?

For Junior Bioinformatics Remote jobs in California, the most frequently searched job titles are:

What cities in California are hiring for Junior Bioinformatics Remote jobs?

Cities in California with the most Junior Bioinformatics Remote job openings:

Junior Computational Biologist (Remote)

Astrix Inc

South San Francisco, CA • On-site, Remote

$30 - $34/hr

Full-time

Re-posted 3 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.
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