Resume

Computational Biologist Resume Example & Writing Guide

Use this Computational Biologist resume example and guide to improve your career and write a powerful resume that will separate you from the competition.

Computational biologists use computer programs to analyze huge amounts of data to solve problems in biology. They’re also called bioinformaticians, bioinformaticists, or bioinformatics specialists.

If you love playing with data but also have a passion for biology, this could be the perfect role for you. Computational biologists use their computer skills to make sense of the massive amounts of information generated by scientists every day.

Here are some tips plus an example to help you write your own fantastic computational biologist resume that hiring managers will love.

Jennifer Thomas
Chicago, IL | (123) 456-7891 | [email protected]
Summary

Driven and innovative computational biologist with experience in data analysis, machine learning, and software development. Proven ability to utilize large data sets to answer complex biological questions. Eager to apply skills in a research-driven environment and contribute to the advancement of knowledge in the life sciences.

Education
University of Illinois at Urbana-Champaign Jun '07
M.S. in Bioinformatics
University of Illinois at Urbana-Champaign Jun '05
B.S. in Biology
Experience
Company A, Computational Biologist Jan '17 – Current
  • Developed and implemented novel computational methods for analyzing single-cell RNA sequencing data to identify cell populations in the human endometrium, which may be useful for predicting embryo implantation potential.
  • Designed and conducted experiments using a combination of microscopy techniques (fluorescence imaging, confocal laser scanning) and image analysis software (ImageJ).
  • Analyzed gene expression data from multiple sources including microarray, RNAseq, qPCR assays to address biological questions related to reproductive health.
  • Collaborated with scientists at other institutions on collaborative projects involving large datasets generated by collaborators outside our lab.
  • Communicated research findings through oral presentations at national conferences as well as journal publications.
Company B, Computational Biologist Jan '12 – Dec '16
  • Developed novel computational methods to identify protein-protein interactions in yeast, which led to the identification of new pathways
  • Conducted large-scale proteomics experiments using mass spectrometry and developed bioinformatics tools for data analysis
  • Analyzed genomic sequence data from human cancer cell lines and identified potential therapeutic targets for drug development
  • Collaborated with biologists on research projects involving genome sequencing, gene regulation, and molecular evolution
  • Designed algorithms that improved the accuracy of predicting protein structures from amino acid sequences by ~30%
Company C, Research Assistant Jan '09 – Dec '11
  • Contributed to a research study regarding the impact of performance-based rewards on performers and audiences as well as assisted with other data collection/analysis, report writing, statistical analysis, and manuscript preparation tasks.
  • Assisted in preparing materials for conferences and workshops including slide presentations, handouts, posters, etc., managed contacts with outside collaborators such as conference presenters and journal reviewers, coordinated logistics for meetings (e.g., booking rooms).
  • Gathered information about venues that are available for performances at our school facilities and assisted with creating an online calendar tool for scheduling venue use across campus departments.
Certifications
  • Bachelor of Science in Biology
  • Master of Science in Bioinformatics
  • Certificate in Genomic Data Science
Skills

Industry Knowledge: Bioinformatics, Genetics, Genomics, Proteomics, Transcriptomics, Bioinformatics
Technical Skills: Linux, Unix, Python, Perl, R, C++, Java, C, LabVIEW, MATLAB
Soft Skills: Communication, Teamwork, Collaboration, Leadership, Time Management, Organization

How to Write a Computational Biologist Resume

Here’s how to write a computational biologist resume of your own.

Write Compelling Bullet Points

Bullet points are the most effective way to showcase your experience and qualifications. But rather than simply listing your responsibilities, you can make your bullet points much more interesting and compelling by using them to tell a story about your work.

For example, rather than saying you “analyzed data to identify trends,” you could say you “analyzed data from patient surveys to identify trends in patient satisfaction and develop new initiatives to improve hospital ratings.”

The second bullet point is much more interesting because it provides more detail about what exactly you did and the outcome of your work.

Identify and Include Relevant Keywords

When you apply for a job as a computational biologist, your resume is likely to go through an applicant tracking system (ATS). This program will scan your resume for certain keywords related to the position you’re applying for. If your resume doesn’t include enough of the right keywords, the ATS might automatically reject your application.

One way to make sure you have the right keywords on your resume is to look at the job posting and take note of the terms they use. Then, try to use those same terms throughout your resume. Here are some commonly used keywords for computational biologist roles:

  • Biostatistics
  • Bioinformatics
  • Biotechnology
  • Molecular Biology
  • Python (Programming Language)
  • MATLAB
  • Linux
  • Genetics
  • R (Programming Language)
  • Sequence Analysis
  • SAS
  • Data Analysis
  • Biochemistry
  • Machine Learning
  • Computational Biology
  • Life Sciences
  • Proteomics
  • MATLAB Programming
  • Cell Culture
  • Statistical Data Analysis
  • Genomics
  • Next-Generation Sequencing (NGS)
  • HPC
  • High-Performance Computing
  • Java
  • Microarray
  • Biostatistics
  • Research
  • Biotechnology Research
  • Scientific Writing

Showcase Your Technical Skills

As a computational biologist, you need to be proficient in a variety of software programs and systems in order to effectively do your job. This might include programs like R, Python, and MATLAB, as well as systems like Linux and Hadoop. Additionally, you should have experience with data mining, machine learning, and modeling.

Recruiters are looking for computational biologists who have a solid understanding of big data concepts and who are familiar with a wide range of software programs and systems. So if you have the relevant skills and experience, be sure to list them prominently on your resume.

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