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Computational Drug Design Jobs in Washington (NOW HIRING)

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

... 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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Computational Drug Design information

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 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 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 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 popular job titles related to Computational Drug Design jobs in Washington?

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

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

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

Infographic showing various Computational Drug Design job openings in Washington as of June 2026, with employment types broken down into 80% Full Time, 17% Part Time, 2% Contract, and 1% Nights. Highlights an 74% Physical, 1% Hybrid, and 25% Remote job distribution.

Computational Biologics Design

AstraZeneca

Gaithersburg, MD

Full-time

Posted 20 days ago


AstraZeneca rating

8.4

Company rating: 8.4 out of 10

Based on 45 frontline employees who took The Breakroom Quiz

22nd of 86 rated pharmaceutical


Job description

Job Description

Role Description

Do you have expertise in, and passion for data science and AI? Would you like to play a pivotal role that impacts the delivery of novel biologics drugs for oncology, respiratory and cardiovascular diseases in a company that follows the science and turns ideas into life changing medicines? Then AstraZeneca might be for you!

The Biologics Engineering team is responsible for the discovery and optimisation of biological candidate drugs to support all therapy area drug discovery pipelines and for the development of in-house biologics discovery platforms and novel drug modalities to support future drug discovery efforts.

Central to this effort are the Biologics Augmented Biologics Design team who are building on existing technologies to advance learning from the large and complex data sets we generate and excitingly the team is growing to meet this challenge. This role provides the opportunity for a talented and motivated computational structural biologist.

Typical Accountabilities

  • Lead the in silico support on pipeline therapeutic projects in collaboration with AZ stakeholders

  • Work collaboratively with data and drug discovery scientists to establish structural analytics workflows for biologics discovery

  • Contribute to the development of an end-to-end data analysis capability within Biologics Engineering team as part of a cross-functional team

  • Drive innovative structural, generative & machine learning methods for the design and optimisation of biologic therapeutics

  • Participate in strategic external collaborations

  • Demonstrate effective communication to translate complex concepts to non-experts in internal and external scientific meetings

Must Have

PhD in relevant field (e.g. Structural Biology, Computer Science, Bioinformatics, Physics and Mathematics)and 2 years experience in Silico Design
Knowledge of computational structural biology and demonstrated application of data analysis methods
Experience with structural modelling platforms (e.g. Schrodinger, Rosetta etc)
Familiarity with antibody discovery & optimisation, protein structures
Skilled in applying generative AI, Machine learning or deep learning to design and optimise proteins
Strong, professional communication skills and excellent attention to detail, capable of developing good working relationships with diverse individuals
Experience working within a team environment
Acts with integrity and does the right thing

Desireable

  • Knowledge of FAIR data principles

  • Experience with the analysis of large structural, sequence and experimental datasets.

Date Posted

27-Jul-2026

Closing Date

20-Aug-2026

Our mission is to build an inclusive environment where equal employment opportunities are available to all applicants and employees. In furtherance of that mission, we welcome and consider applications from all qualified candidates, regardless of their protected characteristics. If you have a disability or special need that requires accommodation, please complete the corresponding section in the application form.


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