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Homology Modeling Jobs (NOW HIRING)

Caltech

Research Scientist

Pasadena, CA · On-site

... across model plants and multiple crop species, and led complex, multi-investigator genome ... Direct experience developing tools that enhance homology-directed repair, targeted integration, DNA ...

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How much do homology modeling jobs pay per hour?

As of Jun 5, 2026, the average hourly pay for homology modeling in the United States is $40.33, according to ZipRecruiter salary data. Most workers in this role earn between $31.25 and $43.51 per hour, depending on experience, location, and employer.

What is homology modeling in bioinformatics?

Homology modeling, also known as comparative modeling, is a computational method used to predict the 3D structure of a protein based on its similarity to one or more proteins with known structures. This technique relies on the assumption that proteins with similar sequences will have similar structures. By aligning the target protein sequence with a related protein (the template), researchers can build a structural model that provides insights into the function and interactions of the target protein. Homology modeling is widely used in drug discovery, protein engineering, and understanding molecular mechanisms when experimental structures are unavailable.

What are the key skills and qualifications needed to thrive as a Homology Modeling Scientist, and why are they important?

To excel as a Homology Modeling Scientist, you need a strong background in structural biology, bioinformatics, and molecular modeling, typically supported by a degree in biochemistry, biophysics, or a related field. Expertise in computational tools like MODELLER, Swiss-Model, and molecular visualization software, as well as familiarity with protein databases, is essential. Analytical thinking, attention to detail, and effective communication are critical soft skills for interpreting results and collaborating with multidisciplinary teams. These competencies ensure accurate protein structure predictions, which are vital for drug discovery and understanding biological mechanisms.

What are some common challenges faced by professionals working in homology modeling, and how can they be addressed?

Professionals in homology modeling often encounter challenges such as limited availability of suitable template structures, inaccuracies in sequence alignments, and difficulties in modeling flexible or poorly conserved regions. Addressing these issues typically involves using multiple templates, carefully refining alignments, and incorporating additional bioinformatics tools to predict loop regions or side-chain conformations. Collaborating with structural biologists and leveraging the latest structural databases can also improve the accuracy and reliability of homology models.
Infographic showing various Homology Modeling job openings in the United States as of May 2026, with employment types broken down into 86% Full Time, 12% Part Time, and 2% Contract. Highlights an 100% Hybrid job distribution, with an average salary of $83,896 per year, or $40.3 per hour.
Principal Scientist, Computational Chemistry

Principal Scientist, Computational Chemistry

Eikon Therapeutics

Millbrae, CA

$204K - $223K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 8 days ago

Job description

Position 

We seek a Principal Scientist in Computational Chemistry with a demonstrated ability of successfully applying in silico technologies to drive the discovery of quality lead-like molecules against hard to drug therapeutic targets. The candidate will apply AI/ML to impact library design, HTS hit identification, virtual screens, and (virtual) hit expansion efforts towards hit-to-lead across multiple projects. The role involves protein modeling, AI co-folded structure/affinity predictions, binding site/ligand-ability assessment, homology-based chemistry mining, virtual screening and purchasable compound procurement. You will daily collaborate closely with biologists, medicinal chemists, software engineers and machine learning experts. As an integral member of our growing Drug Discovery team, you will make a real and direct impact on accelerating the drug discovery process and ultimately benefiting patients. 

About You 

You're a computational chemistry/cheminformatics expert who loves to solve difficult problems and are not discouraged by challenges. You have a passion for drug discovery and thrive in a fast-paced, dynamic environment. You are curious, love challenges, and enjoy pushing the edge of technology to solve important problems with creative solutions. You're collaborative by nature, resourceful, open-minded, data-driven, and can operate with a sense of urgency. 
 

What You'll Do 

  • Deliver virtual screening workflows that leverage physics- and AI-based modeling methods involving ligand- and structure-based methods, ensemble docking, molecular dynamics, and free energy calculations
  • Provide computational chemistry program support across our drug discovery pipeline spanning target selection, HTS, hit identification/calling, hit to lead, and lead optimization
  • Provide guidance on the application of modern cheminformatics, ML/AI methods for library design (e.g. diversity, focused, fragment, DEL) and analyzing large datasets from HTS campaigns to building predictive models from them
  • Routinely employ expert knowledge and analysis of SAR, physiochemical and ADMET properties
  • Work alongside medicinal chemists to further triage emerging hits for synthesis/purchase
  • Collaborate closely with our data science team to integrate cutting edge AI/ML tools into our chemistry and drug discovery processes

Qualifications 

  • PhD in Computational Chemistry or related discipline with +10 years of relevant experience; or Master's plus 18 years of relevant experience; or Bachelor's plus 20 years of relevant experience
  • Expertise in virtual screening, HTS triaging, hit calling, and diversity analysis
  • Expertise in computational chemistry software, such as Schrodinger Suite, Rosetta, AlphaFold, Gromacs, or similar tools
  • Expertise with physics-based methods, molecular dynamics, conformational analysis, free energy perturbation, and quantum mechanics
  • Expertise in cheminformatics data analysis, data mining and machine learning models to solve drug discovery problems
  • Experience with ligand-based design approaches, QSAR, QSPR, multiparameter optimization to rationalize SAR and design novel molecules
  • A track record of publications, patents and/or conference presentations in computational chemistry and/or drug discovery
  • Proficient in scientific programming (e.g. python, KNIME) and data analytics (Spotfire, DataWarrior, Pandas)
  • Excellent problem-solving abilities and the ability to work in a fast-paced, dynamic research environment
  • Strong communication skills with the ability to convey complex scientific concepts to both technical and non-technical stakeholders 

At Eikon, employee compensation also includes bonus and equity compensation, in addition to several generous benefit programs, including:

  • 401k plan with company matching
  • Medical (premiums covered by Eikon at 95%), dental and vision insurance (premiums covered by Eikon at 100%)
  • Mental health and wellness benefits
  • Weeklong summer and winter holiday shutdowns
  • Generous paid time off and holiday policies
  • Life/AD&D Insurance (premiums covered by Eikon at 100%) and optional supplemental employee-paid life/AD&D policies
  • Enhanced parental leave benefit
  • Daily subsidized lunch program when on-site

The expected salary range for this role is $204,000 to $223,250 depending on skills, competency, and the market demand for your expertise.

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