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

As of Jul 16, 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 as a Computational Drug Discovery Design professional, and why are they important?

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 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.

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.
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Computational Drug Discovery Design jobs near you
Infographic showing various Computational Drug Discovery Design job openings in the United States as of July 2026, with employment types broken down into 2% Internship, 71% Full Time, 25% Part Time, 1% Temporary, and 1% Contract. Highlights an 70% Physical, 1% Hybrid, and 29% Remote job distribution, with an average salary of $114,249 per year, or $54.9 per hour.

Head of Computational Drug Design, Cambridge, MA

Isomorphic Labs

Cambridge, MA • On-site, Remote

Other

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

About the Computational Drug Design Team

We are building a dynamic team of Computational Chemists in Cambridge, MA within the Drug Design and Medical Research function. We drive the computational chemistry strategy for our internal portfolio and collaboration projects. Crucially, we partner closely with our AI/ML colleagues, using our domain expertise to augment the Isomorphic Labs Drug Design Engine and leverage its power to accelerate drug design. We foster a supportive, learning-focused environment where every member is valued, and continuous professional development is a priority.

Your Impact

As part of our expansion to Cambridge, MA, we are seeking an experienced and strategic Head of Computational Drug Design to join our foundational Drug Design team. This is a pivotal role for a motivated scientific leader eager to shape the future of drug discovery at the intersection of computational chemistry and artificial intelligence. This role requires a unique blend of deep scientific expertise and the ability to lead both technical projects and high-performing teams, whilst contributing to or leading active drug discovery programs.

You will provide scientific leadership and strategic direction for the Computational Drug Design team, responsible for delivery and guidance of projects to clinical candidate nomination. Additionally, you will oversee and mentor a team of talented Computational Drug Designers, fostering their scientific growth and career development. Working alongside world-leading AI Scientists, you will play a critical role in establishing principles for embedding AI/ML into modern computational chemistry workflows, ensuring seamless integration across ML, Biology, and Chemistry teams.  You will partner with our Head of Chemistry, Drug Design to champion the drug discovery pipeline, overseeing external collaborations (with CROs) and lead programs to deliver critical go/no-go milestones. Critical to this role will be the ability to build highly effective and efficient connectivity with Medicinal Chemistry, Biology and Pre-Clinical Development teams to accelerate pace to the clinic. If you are a skilled Computational Chemist with leadership experience and a passion for applying cutting-edge technology to complex scientific challenges, this role offers an unparalleled opportunity for impact and growth.

What you will do 
  • Apply your knowledge and track record of modern drug design and discovery principles to deliver our Drug Design portfolio. 
  • Provide direct line management for a growing team of Computational Chemists. Set clear goals, provide regular feedback, support their professional development, and foster a collaborative and high-performance team environment.
  • Provide strategic input and technical direction to our AI/ML platform teams. 
  • Collaborate both internally and with third party organisations, interacting within multidisciplinary teams, to support data-driven delivery of high quality scientific solutions to complex technical problems. 
  • Represent the company externally, interacting with existing and prospective collaborators and Contract Research Organizations (CROs). 
  • Prepare detailed scientific proposals and reports to support new and ongoing programs. 
  • Embrace and champion our culture of inclusion and continuous professional development.
 Skills and QualificationsEssential:
  • PhD in Computational Chemistry, Medicinal Chemistry, Synthetic Chemistry, or a related scientific field, or equivalent industrial experience.
  • Solid foundation in computational chemistry with a minimum of 10+ years previous industrial experience within a pharma/biotech/CRO setting.
  • Proven experience leading computational chemistry strategy and execution for multiple drug discovery programs and target classes, and managing high-performing scientific teams.
  • Prior experience of leading drug discovery programs, from hit finding to lead optimisation and candidate selection.
  • Strong expertise in virtual screening, ligand and structure-based drug design using physics-based and ideally AI/ML methods.
  • Proven track record of developing models using ML or deep learning methods.
  • Expertise in writing and implementing Python scripts for analysis and tool development, and/or utilising pipelining tools to support cheminformatics and design workflows.
  • Genuine passion and enthusiasm for applying AI/ML to drug design and how this can transform the field.
  • Demonstrated success managing external collaborations (industry/CROs) and working effectively in cross-functional environments.
  • Growth mindset, adaptability, and eagerness to learn new concepts and techniques.
Nice to Have:
  • Prior experience leveraging machine learning and generative AI methods for hit finding (e.g. ultra-large virtual screening and active learning), molecular design and lead optimisation
  • Strong knowledge of drug design principles, including ADMET and DMPK.
  • Knowledge of modalities such as PROTACs, molecular glues, PPI inhibitors or ADCs.
  • A track record of authorship of relevant scientific manuscripts.

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