ZipRecruiter

Log In

1

Computational Drug Discovery Design Jobs (NOW HIRING)

Novartis

Computational Medicinal Chemist

San Diego, CA · On-site

$138K - $257K/yr

Proven track record of innovation through analogue design, leading to significant impact on discovery projects. * Familiarity with computational drug design tools (e.g. Schrdoinger, CCG, OpenEye, etc ...

JobRx, Inc.

Computational Chemistry Lead

Cambridge, MA · On-site

$119 - $170/hr

Purpose & Scope This role supports drug discovery efforts by applying advanced computational chemistry techniques to design and optimize small-molecule therapeutics. The position requires close ...

New

Transcripta Bio

Scientist, Drug Discovery

Palo Alto, CA · On-site

$120 - $180/hr

Design screening workflows, ensure data integrity, and resolve technical issues efficiently ... computational and therapeutic teams to align experimental outputs with platform requirements.

previous pagenext page

Showing results 21-40

All JobsTechnology JobsData JobsBioinformatics Scientist JobsComputational Drug Discovery Design Jobs

Computational Drug Discovery Design information

See salary details

$40

$54

$74

How much do computational drug discovery design jobs pay per hour?

As of Aug 19, 2026, the average hourly pay for computational drug discovery design in the United States is $54.93, according to ZipRecruiter salary data. Most workers in this role earn between $46.88 and $73.56 per hour, depending on experience, location, and employer.

What is computational drug discovery design?

Computational drug discovery design is the use of computer-based tools and models to identify and optimize potential drug candidates before laboratory testing. It involves simulating molecular interactions, predicting drug-target binding, and analyzing large datasets to accelerate the drug development process. This approach helps researchers save time and resources by focusing experiments on the most promising compounds, ultimately increasing the efficiency and success rate of drug discovery.

What are the key skills and qualifications needed to thrive in computational drug discovery design?

To excel in Computational Drug Discovery Design, you need a solid background in computational chemistry, molecular modeling, and bioinformatics, typically supported by an advanced degree in chemistry, biology, or a related field. Expertise in tools such as molecular docking software (e.g., AutoDock, Schrödinger), programming languages (e.g., Python, R), and familiarity with drug databases are highly valuable. Strong problem-solving skills, attention to detail, and the ability to collaborate across multidisciplinary teams distinguish top performers in this field. These skills are essential for efficiently identifying promising drug candidates and accelerating the drug development process.

What are some common challenges faced by professionals in computational drug discovery design, and how can they be addressed?

A key challenge in computational drug discovery design is managing the complexity and variability of biological data, which can affect the accuracy of predictive models. Professionals often need to validate their computational findings with experimental results, requiring strong collaboration with laboratory scientists. Staying updated with rapidly evolving software tools and algorithms is also essential. To address these challenges, ongoing professional development, interdisciplinary teamwork, and regular communication between computational and experimental teams are highly recommended.

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

AspectComputational Drug Discovery DesignComputational Chemist
CredentialsDegree in chemistry, bioinformatics, or related fields; experience with drug discovery toolsDegree in chemistry, computational chemistry, or related fields; strong programming skills
Work EnvironmentPharmaceutical or biotech industry, research labsResearch labs, academia, industry
Industry UsageFocused on designing new drug candidates and predicting their behaviorAnalyzing chemical structures, modeling molecules, and understanding chemical properties

Computational Drug Discovery Design primarily focuses on developing new drug candidates using computational methods, while Computational Chemist applies similar skills to analyze chemical structures and properties. Both roles require strong chemistry and computational skills but differ in their specific objectives within the drug development process.

More about Computational Drug Discovery Design jobs

What cities are hiring for Computational Drug Discovery Design jobs?

Cities with the most Computational Drug Discovery Design job openings:

What states have the most Computational Drug Discovery Design jobs?

States with the most job openings for Computational Drug Discovery Design jobs include:

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

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

Computational Drug Discovery Design jobs near you
Infographic showing various Computational Drug Discovery Design job openings in the United States as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $114,249 per year, or $54.9 per hour.

Computational Scientist

Tamarind Bio, Inc

San Francisco, CA • On-site

Full-time

Re-posted 29 days ago

Job description

About Tamarind Bio
We enable any scientist to access AI-powered drug discovery. Thousands of scientists from large pharma companies, top biotechs, and academic institutions use Tamarind to design protein drugs, improve industrial enzymes, and create cutting edge molecules that weren't feasible until now.
New AI models are quickly eclipsing physics-based tools in computational drug discovery. Scientists often struggle to fine-tune, deploy, and scale these models, leaving breakthroughs on the table. Tamarind provides a simple interface to the vast array of tools being released daily.
About the Role
We're hiring a Computational Scientist to help curate, build, and scale Tamarind's library of AI-powered drug discovery tools.
In this role, you'll work closely with the founders and engineering team to operationalize cutting-edge models for structure prediction, protein design, docking, scoring, and other core biological AI workloads. You'll help transform fragmented research tools into production-ready workflows that scientists can run reliably at scale.
You'll collaborate directly with customers to understand their discovery challenges and help them leverage Tamarind's platform to run real biological AI pipelines. This often involves chaining multiple tools together, troubleshooting workflows, and identifying opportunities to improve the platform.
This role sits at the intersection of computational biology, machine learning, and scientific infrastructure, and is ideal for someone excited about applying the latest advances in AI to real-world drug discovery programs.
Our techstack:
  • Python, PyTorch, TensorFlow, CUDA, Conda, Docker, AWS (EC2, S3, DynamoDB), molecular modeling tools, protein design frameworks, structural biology tooling, APIs and workflow orchestration.

Week in the Life:
  • Work with founders and engineers to integrate and deploy biological ML models on the Tamarind platform.
  • Build and refine workflows connecting tools like structure prediction, docking, and scoring models.
  • Partner with customers to troubleshoot pipelines and help them run large-scale discovery workflows.
  • Evaluate new research tools and integrate promising models into the platform
    Contribute to improving reliability, performance, and scalability of scientific pipelines

Qualification requirements:
  • Strong background in computational biology, computational chemistry, bioinformatics, or related field
  • Familiarity with ML and physics-based tools in structural biology, molecular dynamics, protein-ligand docking, or virtual screening
  • Experience working with biological data such as molecular structures, compounds, sequences, and databases
  • Programming experience in Python and scientific computing workflows
  • Comfort working with cloud infrastructure and ML tooling (AWS, Docker, CUDA, Conda, PyTorch, TensorFlow)
  • Located in the SF Bay Area or able to relocate
Our Interview Process
We keep our process focused, transparent, and designed to give both sides a clear sense of fit.
1. Recruiter Screen (15-30 minutes) - Virtual
2. Technical Interview (90 minutes) - Virtual
3. Onsite (1 day) - San Francisco

Apply