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Computational Drug Design Jobs in Utah (NOW HIRING)

micro1 AI

Cheminformatics Specialist - Remote

Provo, UT · Remote

$80 - $110/hr

... design considerations. * Build and implement code-based benchmark tasks (e.g., terminal/CLI-based environments) that reflect realistic computational drug discovery scenarios. * Develop reproducible ...

micro1 AI

Bioinformatics Software Engineer

Saint George, UT · Remote

$80 - $110/hr

... design considerations. * Build and implement code-based benchmark tasks (e.g., terminal/CLI-based environments) that reflect realistic computational drug discovery scenarios. * Develop reproducible ...

micro1 AI

Bioinformatics Software Engineer

Provo, UT · Remote

$80 - $110/hr

... design considerations. * Build and implement code-based benchmark tasks (e.g., terminal/CLI-based environments) that reflect realistic computational drug discovery scenarios. * Develop reproducible ...

micro1 AI

Bioinformatics Software Engineer

West Jordan, UT · Remote

$80 - $110/hr

... design considerations. * Build and implement code-based benchmark tasks (e.g., terminal/CLI-based environments) that reflect realistic computational drug discovery scenarios. * Develop reproducible ...

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All JobsComputational Drug Design JobsComputational Drug Design Jobs in Utah

Computational Drug Design information

What are the key skills and qualifications needed to thrive as a computational drug design scientist?

To thrive as a Computational Drug Design scientist, you need a strong background in chemistry, biology, and computer science, typically supported by an advanced degree (e.g., PhD) in a related field. Proficiency with molecular modeling software, cheminformatics tools, and programming languages such as Python or R is essential, along with familiarity with databases like PDB and software such as Schrödinger or MOE. Strong analytical thinking, problem-solving abilities, and effective communication skills help translate computational findings into actionable insights for multidisciplinary teams. These competencies are crucial for efficiently identifying promising drug candidates and supporting data-driven decision-making in pharmaceutical research.

What is computational drug design?

Computational drug design is the use of computer-based methods and simulations to discover, develop, and optimize new pharmaceutical compounds. This field combines chemistry, biology, and computer science to model how potential drug molecules interact with biological targets, such as proteins or enzymes. Techniques like molecular docking, virtual screening, and molecular dynamics are commonly used to predict the efficacy and safety of new drugs before laboratory testing. By leveraging computational tools, researchers can significantly speed up the drug discovery process and reduce costs.

What is the difference between Computational Drug Design vs Medicinal Chemist?

AspectComputational Drug DesignMedicinal Chemist
Required CredentialsDegree in Chemistry, Bioinformatics, or related field; strong computational skillsDegree in Chemistry, Organic Chemistry, or related field; laboratory experience
Work EnvironmentResearch labs, pharmaceutical companies, biotech firms; primarily computer-basedLaboratories, pharmaceutical companies; hands-on chemical synthesis and analysis
Industry UsageDrug discovery, virtual screening, molecular modeling

Computational Drug Design focuses on using computer simulations and modeling to identify potential drug candidates, while Medicinal Chemists are involved in synthesizing and testing chemical compounds in the lab. Both roles are essential in the drug development process but differ in their methods and work environments.

What are some common challenges faced in a computational drug design role, and how can they be addressed?

Professionals in Computational Drug Design often encounter challenges such as managing large and complex datasets, integrating diverse software tools, and ensuring accurate modeling of biological systems. Addressing these challenges typically involves continuous learning to stay updated with the latest algorithms and software, collaborating closely with experimental scientists, and developing strong data management practices. Effective communication and teamwork are also essential, as the role frequently involves working in multidisciplinary teams to translate computational findings into actionable experimental strategies.

What are popular job titles related to Computational Drug Design jobs in Utah?

For Computational Drug Design jobs in Utah, the most frequently searched job titles are:

What job categories do people searching Computational Drug Design jobs in Utah look for?

The top searched job categories for Computational Drug Design jobs in Utah are:

What cities in Utah are hiring for Computational Drug Design jobs?

Cities in Utah with the most Computational Drug Design job openings:

Computational Drug Design jobs near you
Infographic showing various Computational Drug Design job openings in Utah as of August 2026, with employment types broken down into 87% Full Time, 8% Part Time, and 5% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.

AI Training Specialist - Cheminformatics

micro1 AI

West Jordan, UT • Remote

$80 - $110/hr

Part-time

Posted 13 days ago

Job description

Role Title: Computational Biology & Cheminformatics Expert


Role Type: Contractor


Location: Remote


micro1 is engaging Computational Biology & Cheminformatics Experts to contribute their expertise to a customer’s computational drug discovery project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Scope of Work

  1. Analyze and interpret small-molecule and drug discovery datasets using advanced computational biology, bioinformatics, and cheminformatics methods.
  2. Curate, annotate, and validate chemical and biological datasets (e.g., ChEMBL, PubChem, DrugBank) to support AI-driven discovery platforms.
  3. Evaluate compound-target interactions, ADMET properties, and lead optimization strategies by integrating chemical, biological, and clinical data sources.
  4. Provide expert insights on structure-activity and structure-property relationships (SAR/SPR), medicinal chemistry approaches, and experimental design considerations.
  5. Build and implement code-based benchmark tasks (e.g., terminal/CLI-based environments) that reflect realistic computational drug discovery scenarios.
  6. Develop reproducible environments (e.g., using Docker) and automated testing pipelines to ensure task correctness and solvability.
  7. Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance, delivering detailed written feedback and recommendations.


Preferred Qualifications

  1. Advanced expertise in Computational Biology, Cheminformatics, Medicinal Chemistry, Biochemistry, or related fields; advanced degree (PhD, MSc, PharmD) highly valued but not strictly required.
  2. Strong coding proficiency in Python (beyond analysis scripts), with hands-on experience building tools, pipelines, or testable code; familiarity with Git, GitHub, and Docker.
  3. Extensive experience with cheminformatics toolkits and platforms such as RDKit, KNIME, Schrödinger, OpenEye, or MOE.
  4. Proven track record in small-molecule drug discovery, SAR/QSAR evaluation, ADMET prediction, or virtual screening workflows.
  5. Comfort working with public chemical and bioactivity databases and integrating diverse datasets for scientific analysis.
  6. Demonstrated ability to clearly communicate complex chemical and biological concepts in written feedback and reports.
  7. Experience participating in multidisciplinary and/or remote projects; familiarity with AI-assisted coding tools is a plus.

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