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Entry Level Density Functional Theory Jobs (NOW HIRING)

1910

Computational Theoretical Chemist I

Boston, MA · On-site

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 ...

1910

Computational Theoretical Chemist II

Boston, MA · On-site

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 ...

SES

Computational Materials Scientist

Woburn, MA · On-site +1

$180K - $200K/yr

Conduct and oversee DFT (Density Functional Theory), MD (Molecular Dynamics), and QM (Quantum Mechanics) simulations of battery components, including electrolytes, coatings, and electrodes. * Develop ...

1910

Computational Theoretical Chemist II

Boston, MA

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 ...

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Entry Level Density Functional Theory information

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How much do entry level density functional theory jobs pay per hour?

As of Sep 5, 2026, the average hourly pay for entry level density functional theory in the United States is $17.46, according to ZipRecruiter salary data. Most workers in this role earn between $15.62 and $18.99 per hour, depending on experience, location, and employer.

What is an entry level density functional theory job?

Entry level Density Functional Theory (DFT) jobs typically involve using computational chemistry methods to study the electronic structure of molecules and materials. These roles are often suited for recent graduates or those with limited professional experience in computational chemistry or physics. Entry level DFT positions may include tasks such as running simulations, analyzing data, and assisting in research projects under the guidance of senior scientists. Candidates usually need a background in chemistry, physics, materials science, or a related field, along with some experience in computational modeling or quantum chemistry software. These roles are found in academia, research institutions, and industries like pharmaceuticals or materials science.

What are some typical challenges faced by entry level density functional theory researchers, and how can they be addressed?

Entry-level DFT researchers often encounter challenges such as mastering complex computational software, interpreting simulation results, and keeping up with rapidly evolving methodologies. Learning to troubleshoot code errors and efficiently set up simulations can be time-consuming at first. Collaborating closely with senior researchers, participating in group discussions, and utilizing online forums or tutorials can significantly accelerate the learning curve. Over time, hands-on practice and seeking feedback help build confidence and expertise.

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

To thrive as an entry-level DFT researcher, you need a background in physics, chemistry, or materials science, along with foundational knowledge of quantum mechanics and computational modeling. Familiarity with DFT software packages (such as VASP, Quantum ESPRESSO, or Gaussian) and basic programming skills in Python or Fortran are often required. Strong analytical thinking, attention to detail, and effective communication help in interpreting results and collaborating with research teams. These skills and qualifications are crucial for conducting accurate simulations, troubleshooting computational challenges, and contributing to scientific advancements.

What is the difference between Entry Level Density Functional Theory vs Entry Level Computational Chemist?

AspectEntry Level Density Functional TheoryEntry Level Computational Chemist
Required CredentialsBachelor's degree in chemistry, physics, or related field; basic knowledge of quantum mechanicsBachelor's degree in chemistry, chemical engineering, or related; familiarity with computational methods
Work EnvironmentResearch labs, academic institutions, or industry R&D teamsLaboratories, research institutions, or pharmaceutical companies
Industry UsagePrimarily used in theoretical and computational chemistry researchApplied in drug discovery, materials science, and chemical research

Entry Level Density Functional Theory focuses specifically on quantum mechanical calculations to study electronic structures, while Entry Level Computational Chemist has a broader scope, including various computational methods for chemical analysis. Both roles require similar educational backgrounds and are often found in research settings, but their applications differ in focus and complexity.

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Entry Level Density Functional Theory jobs near you
Infographic showing various Entry Level Density Functional Theory job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 89% Full Time, 6% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $36,327 per year, or $17.5 per hour.

Computational Theoretical Chemist I

1910

Boston, MA • On-site

Full-time

PTO

Re-posted 11 days ago

Key responsibilities

  • Own computational theoretical chemistry programs across therapeutic modalities, disease targets, and indications.

  • Provide key computational chemistry insights to support collaboration with Biology, Medicinal Chemistry, ML Engineering, and AI Research teams during drug discovery processes.

  • Teach computational chemistry principles to cross-disciplinary colleagues and assist in improving existing processes for progressing from computational hit to drug candidate.

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 simulations 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 theoretical 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 
  • 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  
  • 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 
  • 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 

  • Relevant industry experience via internship and co-op 
  • Publication records 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