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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in developing and evaluating machine learning models for molecular property prediction, with a strong foundation in data analysis and model interpretability. Capable of collaborating with interdisciplinary teams and effectively communicating research findings.
Highest-signal resume keywords
Machine Learning Model DevelopmentMolecular Data ProcessingPython ProgrammingModel Interpretability MethodsCheminformatics Tools
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine Learning ModelsPredictive Performance EvaluationData AnalysisModel InterpretabilityStructure-Property RelationshipsResearch ContributionsStatistical MetricsMolecular Property PredictionQuantitative AnalysisData Science
Soft Skills
CollaborationCommunicationDocumentationLiterature ReviewTeamwork
Tools & Technologies
RDKitUnix-Based SystemsVersion Control SoftwareGitConversational AI Agents
Industry Keywords
Computational ChemistryCheminformaticsComputational BiophysicsData ScienceGraduate Program Enrollment
Tech Stack
Tools & technologiesPythonUnix
About the role
Key responsibilities & impact- Develop and evaluate machine learning models for molecular property prediction
- Assess predictive performance using appropriate metrics
- Explore approaches to making models accessible through conversational AI agents
- Apply model interpretability methods to investigate how molecular features influence predictions
- Explore structure–property relationships
- Work collaboratively with interdisciplinary teams to execute and implement the project successfully
- Review and summarize project-related literature
- Communicate findings and progress to team members
- Clearly document methods and analyses to enable reproducible research
Requirements
What you’ll need- Must be available to work a full-time schedule
- Expected continued enrollment in an accredited college or university following the internship program / co-op
- Student must be located in the United States for the duration of the internship program
- 18 years or older
- Graduated with a bachelor’s degree from an accredited college or university
- Currently enrolled in an MBA, Master’s, PharmD, or Ph.D. program from an accredited college or university
- Completion of the first year of the applicable graduate program before the internship starts
- Degree in Computational Chemistry, Cheminformatics, Computational Biophysics, Data Science or a similarly quantitative field
- Familiarity with machine learning models for molecular property prediction, including model development and evaluation of predictive performance
- Experience with molecular data processing and analysis using cheminformatics tools such as RDKit
- Familiarity with model interpretability methods for exploring structure-property relationships
- Demonstrated programming and data analysis experience in Python
- Familiarity with Unix-based systems and version control software (Git)
- Track record of research contributions through peer-reviewed publications or presentations at scientific conferences
- Candidates must be authorized to work in the U.S. for the duration of this program
Benefits
Comp & perks- Competitive benefits
- Professional and personal growth and well-being support
- Collaborative culture
- Executive and social networking events
- Community volunteer projects
- Inclusive environment
- Reasonable accommodation for individuals with disabilities
- Equal opportunity employment