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Protein Structure Prediction Jobs (NOW HIRING)

Ohio State University

Research Scientist

Columbus, OH · On-site

Experience with protein structure prediction, protein-ligand interaction modeling, AlphaFold-derived structures, cryo-EM or crystallographic data, or structural bioinformatics. * Experience with ...

Tomorrow Taste

De novo protein design, structure prediction, molecular dynamics, machine learning on biological sequence data, or previous work on receptor binding. Where you'll be This role is based in San Carlos ...

New

Tomorrow Taste

Computational Biologist

Los Angeles, CA · On-site

De novo protein design, structure prediction, molecular dynamics, machine learning on biological sequence data, or previous work on receptor binding. Where you'll be This role is based in San Carlos ...

New

UNC-Chapel Hill

Open Rank

Chapel Hill, NC · On-site

... protein structure prediction, and high-performance computing for large-scale molecular dynamics simulations. 3. Experience with Bioluminescence Resonance Energy Transfer (BRET) or comparable cell ...

Edison Scientific, Inc.

$300/wk

... developability prediction, and functional screening strategy * Build benchmarks and success ... Strong foundation in protein structure, function, stability, and the relationship between sequence ...

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Protein Structure Prediction information

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$17

$33

$51

How much do protein structure prediction jobs pay per hour?

As of Sep 13, 2026, the average hourly pay for protein structure prediction in the United States is $33.06, according to ZipRecruiter salary data. Most workers in this role earn between $21.63 and $40.87 per hour, depending on experience, location, and employer.

What is protein structure prediction?

Protein structure prediction is the process of determining the three-dimensional shape of a protein from its amino acid sequence using computational methods. This is important because a protein’s function is largely determined by its structure, but experimental methods like X-ray crystallography and cryo-EM can be time-consuming and costly. Recent advances in artificial intelligence, such as AlphaFold, have significantly improved the accuracy and accessibility of protein structure prediction, making it an essential tool in biological research and drug discovery.

What are the key skills and qualifications needed to thrive in protein structure prediction, and why are they important?

To thrive in protein structure prediction, you need a strong background in bioinformatics, molecular biology, and computational modeling, often supported by an advanced degree in a related field. Familiarity with tools such as AlphaFold, Rosetta, PyMOL, and experience with programming languages like Python or R are typically required. Analytical thinking, problem-solving abilities, and effective collaboration are crucial soft skills for interpreting data and working in interdisciplinary teams. These skills enable accurate modeling of protein structures, which is vital for advancements in drug discovery and understanding biological processes.

What are some common challenges faced by professionals working in protein structure prediction roles?

One of the main challenges in protein structure prediction is managing the complexity and variability of protein folding, which often requires the integration of large-scale datasets and advanced computational methods. Professionals must also stay current with rapidly evolving algorithms and software tools, and may need to troubleshoot issues related to limited experimental data or ambiguous sequence information. Collaboration with biologists, chemists, and data scientists is frequent, as teams work together to validate predictions and interpret results for downstream applications such as drug discovery.

What other helpful pages are available for Protein Structure Prediction?

Other pages related to Protein Structure Prediction:

Infographic showing various Protein Structure Prediction job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 88% Full Time, 9% Part Time, and 2% Contract. Highlights an 39% Physical, 1% Hybrid, and 60% Remote job distribution, with an average salary of $68,765 per year, or $33.1 per hour.

Scientist, Computational Protein Design

Mountain View, CA • On-site

Adimab
Biotechnology Research and Development • 51 - 200 employees
Learn more about Adimabexternal

$156K - $165K/yr

Full-time

Medical, Retirement

Re-posted 4 days ago

Job description

Role: Scientist, Computational Protein Design
Adimab is the leading technology provider for therapeutic antibody drug discovery, focusing solely on our partnerships without pursuing an internal product pipeline. Since 2009, we have partnered with over 140 pharmaceutical and biotechnology companies, generating more than 650 therapeutic programs, of which more than 85 have entered clinical trials.
Role Overview
The role is on Adimab's computational biology team in Mountain View, CA. Data-driven approaches have been central to the development of the Adimab platform, and the team is actively utilizing and developing modern de novo protein design and generative AI methods to extend its capabilities. You will serve as the computational lead for protein design campaigns, embedded within a world-class team of modeling and wet-bench scientists, with direct access to Adimab's industry-leading experimental capabilities to drive the design-build-test cycle.
Responsibilities
  • Take end-to-end ownership of computational protein design campaigns - from design generation through wet-lab collaboration, analysis of experimental data, and optimization of the design-build-test cycle. Applications span de novo epitope-targeted IgG, VHH, and minibinder design, as well as protein solubilization and stabilization.
  • Partner with wet-lab teams to design experiments that generate custom training data for affinity, epitope, and specificity prediction models. Train and rigorously benchmark resulting models against internal and external baselines.
  • Build and maintain the computational infrastructure supporting both protein design campaigns and model development, including reproducible pipelines and integration of computational outputs with wet-lab data.
  • Track developments in computational protein design and ML; evaluate relevance to Adimab's platform and identify opportunities for integration.
  • Serve as a resource for wet-lab scientists on AI/ML capabilities and best practices, helping antibody and protein engineering teams apply computational design methods.

Needed Upon Hire
  • PhD in Biophysics, Biochemistry, Structural Biology, Computational Biology, or a related field.
  • 2-4 years of post-PhD experience specifically in computational protein or binder design.
  • Strong foundation in the analysis of structural and energetic factors driving protein-protein interactions.
  • Proficiency with structure prediction and generative design tools such as RFAntibody, BindCraft, and Protenix. Crystallography or cryo-EM experience is a plus.
  • Strong Python skills and experience building reproducible analysis and modeling pipelines.
  • Proven track record of publication or patent contribution in applied ML for proteins or computational design.
Pay Range: $156,800 - $165,760 base salary and eligibility for 15% bonus
Come join us!
Our integrated antibody discovery and engineering platform provides unprecedented speed from antigen to purified, full-length human IgGs with exquisite specificity and biophysical behavior. We offer fundamental advantages by delivering diverse panels of antibodies that meet the most demanding standards for affinity, epitope specificity, species cross-reactivity, and developability. We enable our partners to rapidly expand their biologics pipelines through a broad spectrum of technology access arrangements.
As a profitable privately-held biotech company, we take a long-term view on value creation and make substantial investments in technology development, research, and our people. We offer individually tailored compensation packages comprised of a competitive salary, meaningful equity, a 2:1 401(k) match, and comprehensive health care benefits.

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