Computational Chemistry Scientist – Drug Discovery

TCWGlobal; San Diego (CA); On-site; USD 62,000 - 88,000; Full time

Job summary

TCWGlobal is seeking a Computational Chemistry Scientist to support drug discovery programs with computational chemistry, molecular modeling, and AI-driven insights. You will work onsite in San Diego on a 12‑month contract, driving lead identification and optimization through structure‑based design, FEP, and MD analyses.

The role requires hands‑on experience in several computational chemistry areas, strong programming skills, and the ability to communicate complex results to multidisciplinary

Qualifications

• Hands-on experience applying computational chemistry and molecular modeling approaches to drug discovery.
• Experience in protein–ligand docking, post-docking analysis, molecular dynamics, homology modeling, quantum chemistry, pharmacophore analysis, or diversity analysis.
• Strong understanding of physical chemistry, computational chemistry, cheminformatics, molecular modeling, and their application to compound design and optimization.
• Experience using computational methods to support lead identification and optimization within multidisciplinary drug discovery programs.
• Programming or scripting experience using Python, C++, R, or similar languages.
• Familiarity with commercial molecular modeling platforms such as Schrödinger, CCG, OpenEye, or similar tools.
• Ability to interpret computational and experimental results, identify inconsistencies or anomalies, and communicate their scientific implications.
• Strong scientific reasoning, analytical thinking, and problem‑solving skills.
• Ability to independently manage projects and deliver high‑quality work with minimal supervision.
• Excellent written and verbal communication skills with the ability to clearly explain technical concepts and computational results.
• Strong organizational skills and ability to manage multiple deadlines while maintaining accuracy and efficiency.
• Collaborative mindset with the ability to work effectively across multidisciplinary scientific teams.

Responsibilities

• Drive computationally supported drug discovery projects from early lead identification through advanced lead optimization.
• Apply molecular modeling and computational chemistry approaches to design and optimize compounds with balanced target, DMPK, and in‑vivo properties.
• Serve as a subject matter expert in one or more computational discovery approaches.
• Apply molecular modeling techniques including pharmacophore analysis, library design, virtual high‑throughput screening, diversity and similarity analysis, and scaffold hopping.
• Perform protein‑ligand modeling using commercial docking platforms and molecular dynamics methods, including post‑docking analysis.
• Develop and apply machine learning and AI models to predict DMPK and in‑vitro biology endpoints and support multi‑parameter optimization.
• Leverage large chemistry and chemogenomic datasets to generate predictive insights for drug discovery programs.
• Integrate multiple computational approaches to inform compound design strategies.
• Independently drive structure‑based design projects considering target protein flexibility.
• Present computational findings to cross‑functional stakeholders.
• Contribute innovative ideas and advanced methodologies to strengthen capabilities.
• Lead one to two computational technology platforms and develop new methods.

Skills

Computational chemistry

Molecular modeling

Programming (Python/C++/R)

Docking analysis

Molecular dynamics

Cheminformatics

AI/ML in drug discovery

Education

Bachelor's degree in Chemistry

Master's degree in Chemistry

PhD in Computational Chemistry

Tools

Schrödinger

CCG

OpenEye

Job description

Computational Chemistry Scientist — Drug Discovery (Contract)

Pay Rate: Up to $54.49/hour

Duration: 12-Month Temporary Assignment

Hours: Full-Time

Start Date: ASAP

Location: San Diego, CA (Onsite)

Summary

We are seeking an experienced Computational Chemistry Scientist to support drug discovery programs through computationally driven approaches for the design and optimization of novel compounds. In this role, you will apply computational chemistry, molecular modeling, cheminformatics, and advanced computational methods to help identify and optimize compounds with balanced target, DMPK, and in‑vivo properties.

The ideal candidate brings hands‑on experience applying computational methodologies to real‑world drug discovery programs, with expertise in one or more areas such as structure‑based design, free energy perturbation (FEP), virtual screening, molecular dynamics, quantum chemistry, machine learning, or modern AI. This individual will work closely with multidisciplinary project teams, communicate computational insights clearly, and independently drive projects while maintaining a highly collaborative approach.

What You’ll Do

• Drive computationally supported drug discovery projects from early lead identification through advanced lead optimization
• Apply molecular modeling and computational chemistry approaches to design and optimize compounds with balanced target, DMPK, and in‑vivo properties
• Serve as a subject matter expert in one or more computational discovery approaches, including structure‑based design, FEP, virtual screening, quantum chemistry, molecular dynamics, machine learning, or AI
• Apply molecular modeling techniques including pharmacophore analysis, library design, virtual high‑throughput screening, diversity and similarity analysis, and scaffold hopping
• Perform protein‑ligand modeling using commercial docking platforms and molecular dynamics methods, including post‑docking analysis
• Develop and apply machine learning and AI models to predict DMPK and in‑vitro biology endpoints and support more efficient multi‑parameter optimization and compound design
• Leverage large chemistry and chemogenomic datasets, including relevant public‑domain datasets, to generate predictive insights for drug discovery programs
• Integrate multiple computational approaches, including machine learning predictions and structure‑based or ligand‑based modeling, to inform compound design strategies
• Independently drive structure‑based design projects, including consideration of target protein flexibility and other factors affecting compound optimization
• Serve as a computational chemistry representative on multidisciplinary project teams, communicating results and recommendations to support project decision‑making
• Present computational findings, modeling results, and scientific insights to discovery project teams and cross‑functional stakeholders
• Contribute innovative ideas and advanced methodologies to strengthen computational chemistry capabilities and support multiple discovery programs
• Lead or advance one to two computational technology platforms, developing new methods that align with project needs and broader computational chemistry strategies
• Collaborate with Research stakeholders to exchange key findings, align on project strategies, and advance compound development
• Provide training, mentorship, or technical guidance to junior team members as needed

What You Bring

• Bachelor’s degree in Chemistry or a related field with 5+ years of relevant experience
• Master’s degree in Chemistry or a related field with 3+ years of relevant experience
• PhD in Computational Chemistry or a related discipline with relevant industry or research experience

OR

• Hands‑on experience applying computational chemistry and molecular modeling approaches to drug discovery
• Experience in one or more areas including protein‑ligand docking, post‑docking analysis, molecular dynamics, homology modeling, quantum chemistry, pharmacophore analysis, or diversity analysis
• Strong understanding of physical chemistry, computational chemistry, cheminformatics, molecular modeling, and their application to compound design and optimization
• Experience using computational methods to support lead identification and optimization within multidisciplinary drug discovery programs
• Programming or scripting experience using Python, C++, R, or similar languages
• Familiarity with commercial molecular modeling platforms such as Schrödinger, CCG, OpenEye, or similar tools
• Ability to interpret computational and experimental results, identify inconsistencies or anomalies, and communicate their scientific implications
• Strong scientific reasoning, analytical thinking, and problem‑solving skills
• Ability to independently manage projects and deliver high‑quality work with minimal supervision
• Excellent written and verbal communication skills with the ability to clearly explain technical concepts and computational results
• Strong organizational skills and ability to manage multiple deadlines while maintaining accuracy and efficiency
• Collaborative mindset with the ability to work effectively across multidisciplinary scientific teams

Bonus Points If You Have

• Experience with free energy perturbation (FEP) or other advanced structure‑based drug design methodologies
• Postdoctoral experience in computational chemistry or cheminformatics
• Experience developing machine learning or AI models for drug discovery
• Experience working with large‑scale chemistry or chemogenomic datasets
• Experience assessing early‑stage targets, including computational approaches to target druggability
• Experience designing or implementing new computational chemistry methodologies or platforms
• Experience working within pharmaceutical or biotechnology drug discovery programs
• Experience providing technical mentorship or training to junior scientists

TCWGlobal is an equal opportunity employer. We do not discriminate based on age, ethnicity, gender, nationality, religious belief, or sexual orientation.

It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.