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Remote Computer Science Internship Jobs in Hayward, CA

Remote Role Responsibilities * Contribute subject matter expertise to a cutting-edge project with ... Science , AI/ML Research , Computer Science , Game Development , or Mechanical/Aerospace ...

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Remote Computer Science Internship information

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$10

$32

$93

How much do remote computer science internship jobs pay per hour?

As of Aug 17, 2026, the average hourly pay for remote computer science internship in Hayward, CA is $32.40, according to ZipRecruiter salary data. Most workers in this role earn between $14.08 and $39.12 per hour, depending on experience, location, and employer.

What is a remote computer science internship?

A Remote Computer Science Internship is a temporary, virtual position where students or aspiring professionals gain hands-on experience in computer science fields such as software development, data analysis, cybersecurity, or AI. Interns work on real-world projects, collaborate with teams, and develop technical and problem-solving skills—all from a remote location. These internships provide valuable exposure to industry tools, programming languages, and professional workflows, enhancing career prospects.

What kind of support and mentorship can I expect during a remote computer science internship?

Remote Computer Science Interns typically receive regular guidance from designated mentors or team leads through scheduled video calls, chat channels, and collaborative online tools. You'll have access to code reviews, feedback sessions, and opportunities to participate in virtual team meetings, allowing you to learn from experienced professionals and ask questions in real-time. Many organizations also provide onboarding resources, documentation, and community forums to help new interns integrate smoothly. This supportive environment ensures you can develop your skills, overcome remote work challenges, and make meaningful contributions during your internship.

What are the key skills and qualifications needed to thrive in a remote computer science internship, and why are they important?

To thrive as a Remote Computer Science Intern, you should possess a solid understanding of programming languages such as Python, Java, or C++, strong problem-solving abilities, and be actively pursuing or holding a degree in computer science or a related field. Familiarity with version control systems like Git, basic knowledge of software development tools, and exposure to collaborative platforms such as GitHub or Jira are highly valued. Excellent communication, self-motivation, and time management skills enable you to work effectively in a remote environment and stay connected with your team. These competencies are essential for successfully contributing to real-world projects, adapting to remote workflows, and developing professionally during the internship.

What are popular job titles related to Remote Computer Science Internship jobs in Hayward, CA?

For Remote Computer Science Internship jobs in Hayward, CA, the most frequently searched job titles are:

What job categories do people searching Remote Computer Science Internship jobs in Hayward, CA look for?

The top searched job categories for Remote Computer Science Internship jobs in Hayward, CA are:

What cities near Hayward, CA are hiring for Remote Computer Science Internship jobs?

Cities near Hayward, CA with the most Remote Computer Science Internship job openings:

Junior Computational Biologist (Remote)

Astrix Inc

South San Francisco, CA • On-site, Remote

$30 - $34/hr

Full-time

Re-posted 5 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
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