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Entry Level Associate Computational Biologist Jobs

Wisconsin

Cancer Radiation Biologist

Madison, WI · On-site

Oncology focus areas may include radiation biology, cell signaling, genetics, DNA damage and repair ... For an appointment at Associate Professor or Professor rank on tenure track, candidates will meet ...

ORAU

Research Associate 2

Oak Ridge, TN · On-site +1

$35.19 - $48.95/hr

The early career research associate will contribute to the Common Fund Data Ecosystem (CFDE ... D. preferred in Bioinformatics, Biomedical Informatics, Computational Biology, Molecular Biology ...

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How much do entry level associate computational biologist jobs pay per year?

As of Aug 20, 2026, the average yearly pay for entry level associate computational biologist in the United States is $93,988.00, according to ZipRecruiter salary data. Most workers in this role earn between $70,500.00 and $117,000.00 per year, depending on experience, location, and employer.
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Entry Level Associate Computational Biologist jobs near you
Infographic showing various Entry Level Associate Computational Biologist job openings in the United States as of August 2026, with employment types broken down into 68% Full Time, 11% Part Time, 5% Temporary, and 16% Contract. Highlights an 100% In-person job distribution, with an average salary of $93,988 per year, or $45.2 per hour.

Data Scientist - Computational Biology

Penfield Search Partners

Waltham, MA • Hybrid

$63K - $64K/yr

Full-time

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

Contact: Neisha Camacho/Terra Parsons -
No 3rd party candidates
Location: Waltham, MA (Hybrid – 4 days onsite/week)
Penfield Search Partners is partnering with an innovative biotechnology company to identify a Data Scientist – Computational Biology contractor for a six-month assignment. This individual will support drug discovery research by processing, analyzing, visualizing, and interpreting next-generation sequencing (NGS) datasets, with a strong emphasis on transcriptomics and long-read sequencing technologies.

The ideal candidate has hands-on experience with RNA sequencing data, strong computational biology expertise, and enjoys collaborating closely with experimental scientists to generate biological insights that advance therapeutic discovery.

Key Responsibilities

  • Process, analyze, visualize, and interpret NGS datasets, including bulk RNA-seq, single-cell RNA-seq (scRNA-seq), and long-read RNA sequencing data.
  • Perform bioinformatics analyses including quality control, sequence alignment, quantification, differential expression, isoform characterization, splicing analysis, and biological interpretation.
  • Collaborate with cross-functional teams of experimental scientists, computational biologists, and research leaders to support target discovery and validation efforts.
  • Translate computational findings into meaningful biological insights that inform research decisions.
  • Evaluate and implement new bioinformatics tools, analytical methods, and emerging technologies relevant to transcriptomics and functional genomics.
  • Develop scripts, workflows, and analytical pipelines to support reproducible and scalable data analysis.
  • Contribute to study design, analytical strategy, and interpretation of research findings.
  • Present results and communicate complex analyses clearly to technical and non-technical stakeholders.
  • Deliver high-quality work while managing multiple priorities in a collaborative research environment.

Qualifications

  • Education & Experience
  • MS or PhD in Bioinformatics, Computational Biology, Systems Biology, Genomics, or a related scientific discipline.
  • Relevant industry, academic, or postdoctoral research experience in computational biology or bioinformatics.

Required Skills

  • Hands-on experience analyzing NGS datasets, particularly:
  • Bulk RNA-seq
  • Single-cell RNA-seq (scRNA-seq)
  • Long-read RNA sequencing using Nanopore (required)
  • Experience with PacBio sequencing is a plus.
  • Strong understanding of transcriptomics, differential expression analysis, isoform discovery, and RNA splicing analysis.
  • Proficiency in Python and/or R.
  • Experience working in Linux environments and high-performance computing (HPC) or cloud platforms such as AWS.
  • Familiarity with genome annotation resources, biological pathway databases, and systems biology concepts.
  • Commitment to reproducible research, documentation, and version control best practices.

Preferred Experience

  • Experience with additional functional genomics data such as ATAC-seq, ChIP-seq, or PRO-seq.
  • Drug discovery or biotechnology industry experience.
  • Experience collaborating with laboratory scientists in a multidisciplinary research environment.

What We're Looking For

We're seeking someone who is curious, collaborative, and scientifically driven, with excellent communication skills and the ability to work closely with both computational and experimental teams. This individual should be comfortable presenting previous research, explaining analytical approaches, and contributing to a fast-paced drug discovery environment.