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Quantitative Biology Jobs (NOW HIRING)

Swarthmore College

Postdoctoral Researcher

Swarthmore, PA · On-site

$65K - $71K/yr

PhD in biophysics, quantitative biology, bioengineering or closely related field. * Demonstrated working experience with standard cellular and molecular biology work. * Demonstrated mathematical ...

Biohub

Postdoctoral Fellow, Live Tissue Omics

Chicago, IL · On-site

$50K - $68K/yr

Experience with quantitative molecular and cell biology techniques and high-throughput profiling. * Demonstrated expertise in quantitative interpretation of complex, high-dimensional datasets.

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How much do quantitative biology jobs pay per year?

As of Jun 10, 2026, the average yearly pay for quantitative biology in the United States is $90,579.00, according to ZipRecruiter salary data. Most workers in this role earn between $35,000.00 and $119,000.00 per year, depending on experience, location, and employer.

What kinds of projects do Quantitative Biologists typically work on, and who do they collaborate with?

Quantitative Biologists often work on projects involving the analysis of large-scale biological data, such as genomics, proteomics, or ecological datasets, using mathematical and computational models to gain new scientific insights. They frequently collaborate with experimental biologists, data scientists, and software engineers to integrate diverse data sources and validate findings. The role may involve designing experiments, building predictive models, and contributing to publications or product development. Expect a dynamic team environment where interdisciplinary communication is key to solving complex biological problems.

What is a Quantitative Biology job?

A Quantitative Biology job involves applying mathematical, statistical, and computational techniques to analyze biological systems and interpret complex biological data. Professionals in this field work at the intersection of biology, data science, and engineering to model biological processes, develop algorithms, and analyze large-scale datasets, such as genomic or imaging data. These roles are common in academia, biotechnology, pharmaceuticals, and healthcare, contributing to advancements in areas like drug discovery, personalized medicine, and systems biology.

What are the key skills and qualifications needed to thrive in the Quantitative Biology position, and why are they important?

To excel in Quantitative Biology, you typically need a strong background in biology, mathematics, statistics, and programming—often supported by an advanced degree in a related field. Proficiency with computational tools such as R, Python, MATLAB, and bioinformatics software is highly valued, and familiarity with data analysis platforms is often required. Strong analytical thinking, problem-solving abilities, and effective communication skills enable collaboration across multidisciplinary teams. These skills are critical for developing models, interpreting complex biological data, and advancing research or product development in life sciences.

More about Quantitative Biology jobs
What cities are hiring for Quantitative Biology jobs? Cities with the most Quantitative Biology job openings:
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Quantitative Biology jobs near you
Infographic showing various Quantitative Biology job openings in the United States as of June 2026, with employment types broken down into 76% Full Time, 22% Part Time, and 2% Contract. Highlights an 77% Physical, 2% Hybrid, and 21% Remote job distribution, with an average salary of $90,579 per year, or $43.5 per hour.
Xing Lab Post Doctoral Associate

Xing Lab Post Doctoral Associate

University of Pittsburgh

Pittsburgh, PA

$47K - $64K/yr

Other

Posted 5 days ago

Job description

It emerges as an exciting new field both in quantitative biology and computational biology on studying how eukaryotic cells make cell fate decisions and convert between different cell types by integrating big data analyses and mechanistic studies1. My lab has been focusing on putting single cell high throughput (e.g., sequencing and imaging) data analyses within the framework of mechanistic modeling2-8. 

The Xing Lab has an immediate opening for a highly motivated researcher at the postdoc level. The ideal candidate will have a PhD in biological physics, quantitative biology, bioengineering, mathematical biology, or a related field, with demonstrated expertise in using dynamical systems theories, and/or machine learning/AI approaches for studying biological processes through single cell genomics data analyses, and/or mechanistic studies of cellular processes. The researcher will collaborate with other lab members and external collaborators at Harvard, UCLA, UPitt, etc. Competitive candidates for the postdoc are expected to: 

1)    Possess experience in single-cell omics data analysis; 

2)    Bring additional expertise in AI/ML or dynamical systems theory-based modeling, or be willing to collaborate closely with lab members who have these backgrounds; 

3)    Demonstrate strong motivation and enthusiasm for learning new skills; 

4)    Show a record of productivity, including first-author publications.

Preference will be given to applicant expected to receive a PhD degree within half a year or have received within 1-2 years.

After applying, please send CV and a research plan to xing1@pitt.edu. After initial screening, I may ask three reference letters arranged to be sent to me directly.

1.              Xing, J. Reconstructing data-driven governing equations for cell phenotypic transitions: integration of data science and systems biology. Physical Biology 19, 061001 (2022).

2.              Qiu, X. et al. Mapping Transcriptomic Vector Fields of Single Cells. Cell 185, 690-711 (2022).

3.              Hu, S. et al. Epithelial-mesenchymal transition couples with cell cycle arrest at various stages. bioRxiv, 2025.02.24.639880 (2025).

4.              Zachary, R.H. et al. Dynamical modeling reveals RNA decay mediates the effect of matrix stiffness on aged muscle stem cell fate. bioRxiv, 2023.02.24.529950 (2023).

5.              Chen, Y. et al. GraphVelo allows for accurate inference of multimodal velocities and molecular mechanisms for single cells. Nat Commun 16, 7831 (2025).

6.              Wang, W. et al. Live-cell imaging and analysis reveal cell phenotypic transition dynamics inherently missing in snapshot data. Science Advances 6, eaba9319 (2020).

7.              Wang, W., Ni, K., Poe, D. & Xing, J. Transiently Increased Coordination in Gene Regulation During Cell Phenotypic Transitions. PRX Life 2, 043009 (2024).

8.              Wang, W., Poe, D., Yang, Y., Hyatt, T. & Xing, J. Epithelial-to-mesenchymal transition proceeds through directional destabilization of multidimensional attractor. eLife 11, e74866 (2022).

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