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Drug Discovery Intern Computational Jobs (NOW HIRING)

... computational and therapeutic teams to align experimental outputs with platform requirements ... Relevant experience in small molecule drug discovery, including interrogating drug mechanism of ...

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Drug Discovery Intern Computational information

What is a drug discovery intern computational?

A Drug Discovery Intern in Computational Sciences applies computer-based techniques to support drug discovery efforts. This role involves using molecular modeling, machine learning, and bioinformatics to analyze chemical and biological data. Interns may assist in virtual screening, structure-based drug design, and simulations to identify potential drug candidates. They collaborate with scientists to refine computational models and improve drug development processes. Strong programming, data analysis, and scientific problem-solving skills are essential for success in this role.

What kind of projects does a drug discovery intern computational typically work on, and how do they contribute to larger research efforts?

As a Drug Discovery Intern Computational, you can expect to work on projects such as analyzing chemical compound databases, running molecular docking simulations, or processing large biological datasets to identify promising drug candidates. You'll often collaborate with other scientists, including medicinal chemists and biologists, to interpret your computational results and refine hypotheses. Your contributions are integral to accelerating early drug development, as they help narrow down potential leads much faster than traditional laboratory methods. This role offers a hands-on introduction to both scientific research and teamwork within the collaborative environment of a drug discovery team.

What are the key skills and qualifications needed to thrive as a drug discovery intern computational, and why are they important?

To excel as a Drug Discovery Intern Computational, you need a background in biology, chemistry, or a related field, along with strong computational and analytical skills. Familiarity with programming languages like Python or R, molecular modelling software, and data analysis tools is highly beneficial. Excellent problem-solving abilities, attention to detail, and the capacity to work collaboratively are valuable soft skills in this area. These skills enable interns to effectively analyze complex biological data, contribute to ongoing projects, and support innovative drug discovery processes.

More about Drug Discovery Intern Computational jobs

What cities are hiring for Drug Discovery Intern Computational jobs?

Cities with the most Drug Discovery Intern Computational job openings:

What states have the most Drug Discovery Intern Computational jobs?

States with the most job openings for Drug Discovery Intern Computational jobs include:

Infographic showing various Drug Discovery Intern Computational job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 20% Part Time, 2% Contract, and 1% Nights. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution.

Computational Chemistry Scientist - Drug Discovery

TCWGlobal

San Diego, CA • On-site, Remote

$54.49/hr

Full-time

Posted 3 days ago

New


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.

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.