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Entry Level Bioinformatics Software Engineer Jobs in Raleigh, NC

Analyze and interpret small-molecule and drug discovery datasets using advanced computational biology, bioinformatics, and cheminformatics methods. * Curate, annotate, and validate chemical and ...

Analyze and interpret small-molecule and drug discovery datasets using advanced computational biology, bioinformatics, and cheminformatics methods. * Curate, annotate, and validate chemical and ...

Analyze and interpret small-molecule and drug discovery datasets using advanced computational biology, bioinformatics, and cheminformatics methods. * Curate, annotate, and validate chemical and ...

This entry-level position performs basic software development assignments within a specific software functional area or product line. QUALIFICATIONS: BS Engineering/Computer Science or equivalent ...

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Train entry-level software engineers as directed by department management, ensuring they are knowledgeable in critical aspects of their roles. Design and work with complex data models. Mentor less ...

Train entry-level software engineers as directed by department management, ensuring they are knowledgeable in critical aspects of their roles. Design and work with complex data models. Mentor less ...

Software Engineer* *- Level 2* supporting our Software and Electronics/Payloads Department which ... from entry-level to the most senior chief engineers and architects to Product Owners and Scrum ...

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Entry Level Bioinformatics Software Engineer information

See Raleigh, NC salary details

$41.8K

$127.4K

$231.8K

How much do entry level bioinformatics software engineer jobs pay per year?

As of Aug 21, 2026, the average yearly pay for entry level bioinformatics software engineer in Raleigh, NC is $127,394.00, according to ZipRecruiter salary data. Most workers in this role earn between $93,300.00 and $152,600.00 per year, depending on experience, location, and employer.

What is the difference between Entry Level Bioinformatics Software Engineer vs Bioinformatics Data Analyst?

AspectEntry Level Bioinformatics Software EngineerBioinformatics Data Analyst
Required CredentialsBachelor's in Bioinformatics, Computer Science, or related field; programming skillsBachelor's in Bioinformatics, Biology, or related field; data analysis skills
Work EnvironmentDevelops software tools, collaborates with bioinformatics teamsAnalyzes biological data, prepares reports, supports research projects
Employer & Industry UsageBiotech, pharma, research institutionsResearch labs, healthcare, biotech companies

Entry Level Bioinformatics Software Engineers focus on developing and maintaining bioinformatics software tools, requiring programming skills and software development knowledge. Bioinformatics Data Analysts primarily interpret biological data and generate reports, emphasizing data analysis skills. Both roles are common in biotech and research industries but differ in daily tasks and skill sets.

What are the most commonly searched types of Bioinformatics Software Engineer jobs in Raleigh, NC?

The most popular types of Bioinformatics Software Engineer jobs in Raleigh, NC are:

What job categories do people searching Entry Level Bioinformatics Software Engineer jobs in Raleigh, NC look for?

The top searched job categories for Entry Level Bioinformatics Software Engineer jobs in Raleigh, NC are:

Infographic showing various Entry Level Bioinformatics Software Engineer job openings in Raleigh, NC as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $127,394 per year, or $61.2 per hour.

Bioinformatics Software Engineer

micro1 AI

Raleigh, NC • Remote

$80 - $110/hr

Part-time

Posted 18 days ago


Job description

Role Title: Computational Biology & Cheminformatics Expert


Role Type: Contractor


Location: Remote


micro1 is engaging Computational Biology & Cheminformatics Experts to contribute their expertise to a customer’s computational drug discovery project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Scope of Work

  1. Analyze and interpret small-molecule and drug discovery datasets using advanced computational biology, bioinformatics, and cheminformatics methods.
  2. Curate, annotate, and validate chemical and biological datasets (e.g., ChEMBL, PubChem, DrugBank) to support AI-driven discovery platforms.
  3. Evaluate compound-target interactions, ADMET properties, and lead optimization strategies by integrating chemical, biological, and clinical data sources.
  4. Provide expert insights on structure-activity and structure-property relationships (SAR/SPR), medicinal chemistry approaches, and experimental design considerations.
  5. Build and implement code-based benchmark tasks (e.g., terminal/CLI-based environments) that reflect realistic computational drug discovery scenarios.
  6. Develop reproducible environments (e.g., using Docker) and automated testing pipelines to ensure task correctness and solvability.
  7. Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance, delivering detailed written feedback and recommendations.


Preferred Qualifications

  1. Advanced expertise in Computational Biology, Cheminformatics, Medicinal Chemistry, Biochemistry, or related fields; advanced degree (PhD, MSc, PharmD) highly valued but not strictly required.
  2. Strong coding proficiency in Python (beyond analysis scripts), with hands-on experience building tools, pipelines, or testable code; familiarity with Git, GitHub, and Docker.
  3. Extensive experience with cheminformatics toolkits and platforms such as RDKit, KNIME, Schrödinger, OpenEye, or MOE.
  4. Proven track record in small-molecule drug discovery, SAR/QSAR evaluation, ADMET prediction, or virtual screening workflows.
  5. Comfort working with public chemical and bioactivity databases and integrating diverse datasets for scientific analysis.
  6. Demonstrated ability to clearly communicate complex chemical and biological concepts in written feedback and reports.
  7. Experience participating in multidisciplinary and/or remote projects; familiarity with AI-assisted coding tools is a plus.