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Computational Drug Design Jobs (NOW HIRING)

Achira

CADD / Application Scientist

New York, NY · On-site

You have significant experience in CADD, structure-based drug design, computational chemistry, medicinal chemistry collaboration, or related work in drug discovery. * You have experience supporting ...

1910

Computational Theoretical Chemist II

Boston, MA · On-site

Own computational chemistry programs across therapeutic modalities, disease targets, and ... Drug Design Development Packages (e.g., EG, Schrodinger, MOE, CRESSET) * Experience working with ...

1910

Computational Theoretical Chemist I

Boston, MA

Own computational theoretical chemistry programs across therapeutic modalities, disease targets ... Drug Design Development Packages (e.g., EG, Schrodinger, MOE, CRESSET) * Experience working with ...

1910

Computational Theoretical Chemist III

Boston, MA · On-site

Own computational chemistry programs across therapeutic modalities, disease targets, and ... Drug Design Development Packages (e.g., EG, Schrodinger, MOE, CRESSET) * Experience working with ...

1910

Computational Theoretical Chemist II

Boston, MA · On-site

Own computational chemistry programs across therapeutic modalities, disease targets, and ... Drug Design Development Packages (e.g., EG, Schrodinger, MOE, CRESSET) * Experience working with ...

1910

Computational Theoretical Chemist I

Boston, MA

Own computational theoretical chemistry programs across therapeutic modalities, disease targets ... Drug Design Development Packages (e.g., EG, Schrodinger, MOE, CRESSET) * Experience working with ...

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How much do computational drug design jobs pay per hour?

As of Jun 7, 2026, the average hourly pay for computational drug 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 are the key skills and qualifications needed to thrive as a Computational Drug Design scientist, and why are they important?

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 states have the most Computational Drug Design jobs? States with the most job openings for Computational Drug Design jobs include:
Infographic showing various Computational Drug Design job openings in the United States as of May 2026, with employment types broken down into 92% Full Time, and 8% Contract. Highlights an 92% In-person, and 8% Remote job distribution, with an average salary of $114,249 per year, or $54.9 per hour.

Principal Scientist, Computational Chemistry

Deep Apple Therapeutics, Inc

South San Francisco, CA • On-site, Remote

Full-time

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

Job description

About Us Deep Apple Therapeutics, part of the Apple Tree Partners (ATP) portfolio, is a Bay Area biotechnology company focused on accelerating drug discovery by integrating molecular docking and structural biology with advanced computer-aided drug design (CADD) technologies. Our state-of-the-art platform combines advanced computational modeling, large-scale compound docking, cryo-EM-based structural biology, and deep learning to drive the efficient identification and development of novel therapeutics. Role Description We are seeking an experienced Computational Scientist to support and advance our computational initiatives in virtual hit discovery and traditional CADD for our portfolio programs. You will join a collaborative team of computational chemists, data scientists, machine learning engineers and medicinal chemists to integrate deep learning models into our drug discovery pipeline. This role will enhance our virtual screening capabilities, optimize molecular design, and facilitate cross-functional collaboration to translate computational insights into viable therapeutic leads. The ideal candidate will bring more than five years of expertise in computational modeling and proven support of drug discovery teams. Key Responsibilities
  • Lead the implementation of virtual hit discovery, including ligand-based and structure-based modeling, on a program-by-program basis.
  • Deploy deep learning models, including generative AI for molecular design, to predict molecular properties, binding affinities, and ADMET profiles for portfolio programs.
  • Collaborate closely with biology, medicinal chemistry, and machine learning teams to validate computational predictions through iterative feedback loops to accelerate pipeline programs.
  • Drive strategic initiatives, including partnerships with academic institutions, technology companies, and CROs, to strengthen our virtual hit discovery capabilities.
  • Stay current with emerging technologies in computational chemistry and deep learning, incorporating them into our pipeline to maintain a competitive edge.
  • Manage project timelines, budgets, and resources while ensuring compliance with data integrity and intellectual property standards.
Required Qualifications and Skills
  • Ph.D. in Computational Chemistry, Cheminformatics, Bioinformatics, or a related field.
  • Minimum of 5 years of professional experience in computational modeling within the biotechnology or pharmaceutical industry, including at least 1-2 years in a computational program leadership role.
  • Strong track record in virtual hit discovery and/or CADD, with demonstrated success leading to IND-ready assets.
  • Proficiency in programming languages such as Python, with extensive experience in data analysis, machine learning pipelines, and high-performance computing.
  • Excellent communication skills, with the proven ability to translate complex technical concepts to non-expert audiences.
At Deep Apple, we value diversity, encourage professional growth, and provide competitive benefits and compensation. Deep Apple is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

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