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Intern Density Functional Theory Scientist Jobs (NOW HIRING)

1910

Computational Theoretical Chemist III

Boston, MA · On-site

... density functional theory (DFT) approaches, molecular dynamics (MD) simulations, including both ... Strong desire to collaborate with AI scientists, data scientists, medicinal chemists, and ...

University of South Carolina

Post Doctoral Fellow

Los Angeles, CA

$53K - $73K/yr

  • Medical

  • Life

  • Retirement

  • PTO

... Sciences Department CAS Chemistry and Biochemistry Location of Vacancy Part/Full Time Full Time ... on combining density functional theory calculations and machine learning (ML) to model the life ...

Ucf

Postdoctoral Scholar, Physics

Orlando, FL · On-site

  • PTO

... first-principles density functional theory (DFT), grand canonical DFT (GC-DFT) calculations ... D. in Physics, Materials Science, Chemistry, Chemical Engineering or related field is required.

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Intern Density Functional Theory Scientist information

What does an intern density functional theory scientist do?

An Intern Density Functional Theory (DFT) Scientist assists in conducting computational research by applying DFT methods to study the electronic structure of atoms, molecules, and materials. They typically work under the supervision of experienced scientists, running simulations, analyzing data, and helping interpret results to understand material properties or chemical reactions. The internship provides hands-on experience with quantum chemistry software, coding, and scientific problem-solving, making it valuable for students interested in materials science, chemistry, or physics.

What are the key skills and qualifications needed to thrive as an intern density functional theory scientist, and why are they important?

To thrive as an Intern Density Functional Theory (DFT) Scientist, you need a solid background in quantum chemistry, physics, or materials science, often demonstrated through relevant coursework or research experience. Familiarity with computational chemistry software (such as VASP, Quantum ESPRESSO, or Gaussian) and programming languages like Python or Fortran is typically required. Strong analytical thinking, attention to detail, and effective communication skills help you interpret results and collaborate within research teams. These skills and qualities are crucial for conducting accurate simulations, contributing to scientific advancements, and working efficiently in research environments.

What types of projects and responsibilities can an intern density functional theory scientist expect during their internship?

As an Intern Density Functional Theory (DFT) Scientist, you will typically assist with computational modeling and simulations of materials, molecules, or chemical reactions using DFT methods. Your daily tasks may include running calculations, analyzing electronic structure data, preparing reports, and collaborating with senior scientists to interpret results. Interns often contribute to ongoing research projects, participate in group meetings, and may have the opportunity to co-author scientific papers. This role provides a valuable opportunity to develop practical skills in quantum chemistry software and to gain insight into how theoretical methods support experimental research in both academic and industrial settings.
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Infographic showing various Intern Density Functional Theory Scientist job openings in the United States as of August 2026, with employment types broken down into 1% Internship, 1% As Needed, 87% Full Time, 6% Part Time, and 5% Contract. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution.

Computational Theoretical Chemist III

1910

Boston, MA • On-site

Full-time

Re-posted 19 days ago

Job description

Company Overview

We are the only AI-native biotech, pioneering small and large molecule therapeutics discovery by integrating massive multimodal data, frontier AI models, and high-throughput lab automation into an infrastructure for AI-enabled drug discovery.

We hire top 1% talent to join our interdisciplinary team of scientists, engineers, researchers, operators, innovators, drug developers, business professionals, and technologists.

Join us to build the world's first AI infrastructure for tech-enabled drug discovery and to deliver a pipeline of diverse drug modalities for all major disease areas.

Computation is revolutionizing drug discovery. Advances in big chemical data, massive computing power, artificial intelligence, and molecular dynamics simulation are changing the way we develop new drugs. At 1910 , we put computation at the heart of drug discovery, blending expertise in computational chemistry, structural biology, pharmacology, data science, and software engineering to develop drugs for previously undruggable targets.

Role description

  • Own computational chemistry programs across therapeutic modalities, disease targets, and indications
  • Ensure effective collaboration with the Biology and Medicinal Chemistry teams by providing key computational chemistry insights to aid in the Hit-to-Lead and Lead Optimization phases of drug discovery operations
  • Ensure effective collaboration with the ML Engineering and AI Research team by providing key computational chemistry insights to aid in the development of AI/ML models for drug discovery as well as the incorporation of those models into drug discovery operations
  • Teach key computational chemistry principles to your cross-disciplinary colleagues from Medicinal Chemistry, AI Research, Machine Learning Engineering, Cell Biology, and Pharmacology
  • Manage day-to-day operations of the Computational Theoretical Chemistry Team, mentor junior staff, and represent the team in senior leadership meetings
  • Partner to improve 1910's existing process for progressing from computational hit to experimental hit to lead to drug candidate
  • Co-author provisional patents and peer-reviewed research papers
  • Progress a virtual hit to a biochemical/cellular hit
  • Validate a cellular hit in a clinically relevant animal model of disease
  • Update provisional patents with the animal model data
  • Nominate a lead candidate for progression into IND-enabling studies
  • Attend and present research at conferences and events related to computational modeling in drug discovery

Qualifications

  • Ph.D. in computational chemistry or related discipline
  • 3+ years of relevant industry experience within drug discovery or biotechnology
  • Played a key role in advancing a drug discovery program from early research phases to clinical development.
  • In-depth knowledge and hands-on experience with quantum chemical (QC) methods, including semi-empirical and density functional theory (DFT) approaches, molecular dynamics (MD) simulations, including both standard MD and enhanced sampling techniques such as metadynamics, umbrella sampling, and replica exchange MD, free energy simulations such as FEP and TI, and QM/MM methodologies for small and large molecular systems
  • Strong understanding of key concepts, including potential energy surfaces (PES), intermolecular and intramolecular forces/interactions, force fields, molecular properties, thermodynamic properties, solvation models (implicit/explicit), and conformational sampling
  • Proficiency in analyzing molecular properties such as solvation free energy, dipole moments, vibrational frequencies, electrostatic potential, charge distribution, and more.
  • Deep knowledge of implicit and explicit solvent models, with extensive experience modeling solvent effects on molecular systems and chemical reactions in various environments
  • Extensive experience in using and troubleshooting software tools for QC calculations (e.g., ORCA, xTB, CREST, etc.), MD simulations (e.g., GROMACS, OpenMM, etc.), Drug Design Development Packages (e.g., EG, Schrodinger, MOE, CRESSET)
  • Experience working with HPC Clusters and cloud-based services like (e.g., Microsoft AZURE, AWS)
  • Ability to optimize computational simulation protocols for efficient resource usage
  • Proven experience working with small organic molecules and large biomolecular systems (e.g., peptides, proteins, etc.) for property prediction, conformational analysis, and structure-activity relationships (SAR)
  • Hands-on experience with Python and Bash scripting for automating workflows and data analysis
  • Familiarity with cheminformatics toolkits such as RDKit for molecular property prediction and data management
  • Basic knowledge of machine learning (ML) techniques applied to molecular property prediction, virtual screening, and related tasks
  • Strong desire to collaborate with AI scientists, data scientists, medicinal chemists, and biologists to interpret computational results and guide experimental design
  • Clear and effective communication of complex scientific ideas through reports, presentations, and publications

Nice to Haves

  • Publications in computational chemistry related to drug discovery

#LI-Onsite

Diversity and Inclusion (1910's Promise)

At 1910, we believe that a diverse, equitable, and inclusive workplace furthers relevance, resilience, and longevity. We encourage people from all backgrounds, ages, abilities, and experiences to apply. 1910 is proud to be an equal-opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. If, due to a disability, you need an accommodation during any part of the interview process, please let your recruiter know. While 1910 supports visa sponsorship, sponsorship opportunities may be limited to certain roles and skills.

Benefits and Perks

  • Competitive compensation package
  • Above market benefits
  • Generous vacation and parental leave
  • Super cool team building activities
  • Great colleagues