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How much do high throughput screening postdoc jobs pay per hour?

As of Jun 6, 2026, the average hourly pay for high throughput screening postdoc in the United States is $39.41, according to ZipRecruiter salary data. Most workers in this role earn between $21.88 and $63.94 per hour, depending on experience, location, and employer.

What is a High Throughput Screening Postdoc?

A High Throughput Screening (HTS) Postdoc is a postdoctoral researcher who specializes in using automated technologies to rapidly test large libraries of chemical compounds, genes, or biomolecules for biological activity. Their work is crucial in drug discovery and functional genomics, as it helps identify potential candidates for further research or therapeutic development. These scientists often work in academic, pharmaceutical, or biotechnology settings, designing and conducting experiments, analyzing large datasets, and collaborating with multidisciplinary teams.

What are the key skills and qualifications needed to thrive as a High Throughput Screening Postdoc, and why are they important?

To thrive as a High Throughput Screening Postdoc, you need a strong background in molecular biology or chemistry, experience in assay development, and typically a Ph.D. in a relevant field. Familiarity with automation platforms, liquid handling robotics, data analysis software, and screening technologies is essential. Strong problem-solving skills, attention to detail, and effective communication are critical soft skills for collaborating with multidisciplinary teams and interpreting complex data. These competencies are vital for designing robust experiments, generating reliable data, and driving drug discovery or biological research projects forward.

What is the difference between High Throughput Screening Postdoc vs High Throughput Screening Scientist?

AspectHigh Throughput Screening PostdocHigh Throughput Screening Scientist
CredentialsPhD in relevant fieldTypically requires a PhD or equivalent experience
Work EnvironmentAcademic or research institutionPharmaceutical or biotech industry
Employer & IndustryUniversities, research institutesBiotech, pharma companies
Primary FocusResearch, developing new screening methodsApplying screening techniques to drug discovery

While both roles involve high throughput screening techniques and require advanced degrees, the High Throughput Screening Postdoc typically focuses on research and method development in academic or research settings. In contrast, the High Throughput Screening Scientist applies these techniques within industry to support drug development and product pipelines.

What are some common challenges faced by a High Throughput Screening Postdoc, and how can they be addressed?

High Throughput Screening (HTS) Postdocs often encounter challenges such as managing large volumes of experimental data, troubleshooting automation equipment, and optimizing assay conditions for reliability and reproducibility. Effective communication and collaboration with multidisciplinary teams, including chemists, biologists, and data scientists, are essential to address these challenges. Staying organized, utilizing robust data management tools, and proactively seeking feedback from colleagues can help ensure successful project outcomes and continuous learning.
Infographic showing various High Throughput Screening Postdoc job openings in the United States as of May 2026, with employment types broken down into 3% Internship, 88% Full Time, 3% Part Time, 3% Temporary, and 3% Contract. Highlights an 100% In-person job distribution, with an average salary of $81,974 per year, or $39.4 per hour.
Postdoctoral Appointee - Computational and Systems Biology

Postdoctoral Appointee - Computational and Systems Biology

Argonne National Laboratory

Lemont, IL

$70K - $117K/yr

Full-time

Posted 3 days ago

Job description

The Data Science Learning Division at Argonne National Laboratory is seeking a postdoctoral researcher to conduct cutting-edge computational and systems biology research. The primary focus of this role will be exploring how intrinsically disordered proteins (IDPs) mediate signaling mechanisms, with a particular emphasis on cancer therapeutics. Supported by a multi-year ARPA-H grant, this project aims to revolutionize the development of therapeutic platforms for IDPs, creating significant advancements in cancer research and treatment strategies.

As part of a collaborative initiative with the University of Chicago Comprehensive Cancer Center, the postdoctoral researcher will work closely with a multidisciplinary team of computational and experimental biologists. The team is dedicated to developing innovative therapeutic strategies for targeting IDPs, including biologics such as protein-protein inhibitors, Proteolysis-targeting chimeras (PROTACs), nanobodies, and more.

Key Responsibilities:

  • Develop foundational models to describe IDP interactions under various physiological conditions, both normal and cancer related
  • Use these models to iteratively design, validate, and refine experiments, leading to effective therapeutic strategies targeting IDPs
  • Collaborate on the development of open-source machine learning tools to support these therapeutic designs
  • Work closely with high-throughput screening teams at the University of Chicago, automating screening protocols in partnership with Argonne National Laboratory
  • Drive research at the intersection of automation, robotics, generative AI, and computational simulations, leveraging the latest advancements in computing infrastructure

Additional Responsibilities:

  • Exercise independent judgment in research activities and possess strong writing skills
  • Gain experience developing machine learning models at a world-class high-performance computing facility

The candidate will have access to state-of-the-art computing resources, including:

  • NVIDIA DGX-2 Systems: Powerful platforms for AI and deep learning (details: NVIDIA DGX-2)
  • Intel-based Aurora Supercomputer: A next-generation supercomputing system (details: Aurora Supercomputer)
  • Additional advanced compute architectures designed for machine learning and AI workflows
  • In addition to computational resources, the postdoctoral researcher will have access to dedicated wet-lab facilities at the University of Chicago and Argonne National Laboratory's Biosciences Division, allowing for seamless computational and experimental research integration

Position Requirements

  • A recent or soon to be completed PhD within the last 0-5 years
  • Computational Biology: Strong background in systems biology and regulatory network modeling
  • Interdisciplinary Collaboration: Experience working across disciplines with computational biologists, computer scientists, and experimental biologists
  • Assay Expertise: Functional understanding of quantitative and high-throughput assays, particularly in biological signaling and screening contexts
  • Machine Learning & Statistics: Proficiency in machine learning, statistical modeling, and quantitative methods for multi-omics data analysis
  • Molecular Simulations: Expertise with molecular simulation tools like OpenMM, AMBER, Gromacs, and NAMD
  • Deep Learning Development: Experience developing, validating, and deploying deep learning models, especially using Pytorch
  • Multi-Omic Data Representation: Ability to build deep representations of multi-omic data
  • Programming Proficiency: Strong knowledge of Python, C/C++, Julia, and other relevant programming languages
  • Ability to model Argonne's core values of impact, safety, respect, integrity, and teamwork.

Job Family

Postdoctoral

Job Profile

Postdoctoral Appointee

Worker Type

Long-Term (Fixed Term)

Time Type

Full timeThe expected hiring range for this position is $70,758.00-$117,925.00.

Please note that the pay range information is a general guideline only. The pay offered to a selected candidate will be determined based on factors such as, but not limited to, the scope and responsibilities of the position, the qualifications of the selected candidate, business considerations, internal equity, and external market pay for comparable jobs. Additionally, comprehensive benefits are part of the total rewards package.

Click here to view Argonne employee benefits!

As an equal employment opportunity employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a safe and welcoming workplace that fosters collaborative scientific discovery and innovation. Argonne encourages everyone to apply for employment. Argonne is committed to nondiscrimination and considers all qualified applicants for employment without regard to any characteristic protected by law.

Argonne employees, and certain guest researchers and contractors, are subject to particular restrictions related to participation in Foreign Government Sponsored or Affiliated Activities, as defined and detailed in United States Department of Energy Order 486.1A. You will be asked to disclose any such participation in the application phase for review by Argonne's Legal Department.

All Argonne offers of employment are contingent upon a background check that includes an assessment of criminal conviction history conducted on an individualized and case-by-case basis. Please be advised that Argonne positions require upon hire (or may require in the future) for the individual be to obtain a government access authorization that involves additional background check requirements. Failure to obtain or maintain such government access authorization could result in the withdrawal of a job offer or future termination of employment.

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