ZipRecruiter

Log In

1

Junior Computational Structural Biology Jobs (NOW HIRING)

Jobs for Humanity

Data Science Managers

Piscataway, NJ · On-site

We are seeking an expert in computational and/or experimental structural biology with an outstanding record of accomplishment and excellent future promise working at the interface between biology ...

Battelle

Computational Biologist

Columbus, OH · On-site

S. plus 10 years of experience in biochemistry, biophysics, computational biology, structural biology, or a closely related field * Deep expertise in computational protein engineering, including AI ...

next page

Showing results 1-20

All JobsScience JobsBiology JobsScientist JobsJunior Computational Structural Biology Jobs

Junior Computational Structural Biology information

See salary details

$7

$26

$47

How much do junior computational structural biology jobs pay per hour?

As of Sep 3, 2026, the average hourly pay for junior computational structural biology in the United States is $26.96, according to ZipRecruiter salary data. Most workers in this role earn between $16.35 and $33.17 per hour, depending on experience, location, and employer.

What is the difference between Junior Computational Structural Biology vs Junior Bioinformatics Analyst?

AspectJunior Computational Structural BiologyJunior Bioinformatics Analyst
Required CredentialsBachelor's or Master's in Bioinformatics, Computational Biology, or related fieldsBachelor's or Master's in Bioinformatics, Computer Science, or related fields
Work EnvironmentResearch labs, biotech companies, academic institutionsResearch institutions, healthcare, biotech firms
Industry UsageStructural modeling, molecular dynamics, protein analysisGenomic data analysis, data management, software development
Common Search/ComparisonYesYes

Junior Computational Structural Biology focuses on analyzing and modeling the 3D structures of biological molecules, often requiring skills in structural bioinformatics and molecular simulations. In contrast, Junior Bioinformatics Analysts typically handle large-scale genomic or proteomic data, emphasizing data analysis and software tools. Both roles share foundational bioinformatics skills but differ in their specific focus areas and applications.

More about Junior Computational Structural Biology jobs

What cities are hiring for Junior Computational Structural Biology jobs?

Cities with the most Junior Computational Structural Biology job openings:

What are the most commonly searched types of Computational Structural Biology jobs?

The most popular types of Computational Structural Biology jobs are:

What states have the most Junior Computational Structural Biology jobs?

States with the most job openings for Junior Computational Structural Biology jobs include:

What job categories do people searching Junior Computational Structural Biology jobs look for?

The top searched job categories for Junior Computational Structural Biology jobs are:

Junior Computational Structural Biology jobs near you
Infographic showing various Junior Computational Structural Biology job openings in the United States as of August 2026, with employment types broken down into 92% Full Time, 5% Part Time, 2% Contract, and 1% Nights. Highlights an 90% Physical, 3% Hybrid, and 7% Remote job distribution, with an average salary of $56,068 per year, or $27 per hour.

Junior Computational Biologist (Remote)

Astrix Inc

South San Francisco, CA

$30 - $34/hr

Full-time

Re-posted 22 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

Apply