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Molecular Docking Jobs (NOW HIRING)

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 ...

Expertise in structure-based drug design (SBDD), including docking, pharmacophore modeling, virtual screening, and molecular dynamics. * 3+ years of experience with ligand-based modeling (QSAR, 2D/3D ...

Postdoctoral Fellow

Huntington, WV

$47K - $64K/yr

Apply computational tools (docking, molecular dynamics) or experimental methods to design and screen small-molecule, peptide, or fragment-based inhibitors against target proteins. * Assay Development:

Postdoctoral Fellow

Huntington, WV · On-site

$47K - $64K/yr

Apply computational tools (docking, molecular dynamics) or experimental methods to design and screen small-molecule, peptide, or fragment-based inhibitors against target proteins. * Assay Development:

Showing results 41-60

Molecular Docking information

What is molecular docking?

A molecular docking job involves using computational techniques to predict the interaction between molecules, such as a drug candidate and a target protein. Researchers in this field use specialized software to model binding affinities, optimize molecular structures, and analyze potential therapeutic effects. This role is often found in pharmaceutical research, bioinformatics, and drug discovery, requiring expertise in molecular modeling, chemistry, and computational biology.

What does a typical day look like for someone working in molecular docking?

A typical day in Molecular Docking often involves running computational simulations to predict how small molecules interact with biological targets, analyzing and interpreting the resulting data, and preparing reports or presentations for research teams. You may also spend time troubleshooting software issues, developing scripts to automate workflows, and staying up to date with the latest scientific literature. Collaboration is common, as you’ll likely work closely with medicinal chemists, structural biologists, and other computational scientists to refine hypotheses and guide experimental design. This multifaceted environment provides opportunities to continually learn and apply new techniques, making the day-to-day work both intellectually stimulating and impactful.

What are the key skills and qualifications needed to thrive in molecular docking?

To thrive in a Molecular Docking role, you need strong expertise in computational chemistry, structural biology, and molecular modeling, often supported by an advanced degree in a related field. Familiarity with molecular docking software (such as AutoDock or Schrödinger Suite), programming languages (like Python or R), and experience with high-performance computing are typically required. Attention to detail, analytical thinking, and effective communication are valuable soft skills for collaborating and presenting complex findings. These capabilities are essential for accurately predicting molecular interactions, driving scientific discovery, and contributing to successful multidisciplinary projects.

Is molecular docking difficult?

Molecular docking is a specialized task within computational chemistry and drug discovery that involves predicting how molecules interact. It requires knowledge of chemistry, biology, and proficiency with software tools, making it challenging for beginners but manageable with training and experience. Success depends on understanding molecular structures, algorithms, and data analysis techniques.
More about Molecular Docking jobs

What cities are hiring for Molecular Docking jobs?

Cities with the most Molecular Docking job openings:

What states have the most Molecular Docking jobs?

States with the most job openings for Molecular Docking jobs include:

Infographic showing various Molecular Docking job openings in the United States as of August 2026, with employment types broken down into 67% Full Time, and 33% Contract. Highlights an 67% In-person, and 33% Remote job distribution.

Computational Chemistry Scientist - Drug Discovery

TCWGlobal

San Diego, CA • On-site, Remote

$54.49/hr

Contractor

Posted 12 days ago


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

OR

• Master's degree in Chemistry or a related field with 3+ years of relevant experience

OR

• PhD in Computational Chemistry or a related discipline with relevant industry or research experience

• 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.

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