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Computational Modeling Scientist Jobs (NOW HIRING)

1910

Computational Theoretical Chemist II

Boston, MA · On-site

... 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 ...

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$50.5K

$111.3K

$137.5K

How much do computational modeling scientist jobs pay per year?

As of Jun 26, 2026, the average yearly pay for computational modeling scientist in the United States is $111,343.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,500.00 and $137,000.00 per year, depending on experience, location, and employer.

What are the typical day-to-day responsibilities of a Computational Modeling Scientist?

As a Computational Modeling Scientist, your daily tasks often include designing and implementing mathematical models or simulations to analyze complex systems, running computational experiments, and refining models based on data analysis. You will collaborate closely with multidisciplinary teams, including scientists, engineers, and sometimes clients, to ensure your models address real-world challenges. Preparing technical documentation, presenting findings, and keeping up with relevant scientific literature are also common parts of the role. The work environment is typically research-focused, either in academic, government, or industrial settings, where teamwork and effective communication are highly valued.

What is the meaning of computational?

In the context of a Computational Modeling Scientist, 'computational' refers to the use of computer-based methods and algorithms to simulate, analyze, and solve complex scientific problems. It involves programming, data analysis, and modeling techniques to understand systems across various fields such as biology, physics, or engineering.

What are the key skills and qualifications needed to thrive in the Computational Modeling Scientist position, and why are they important?

To thrive as a Computational Modeling Scientist, you need a solid background in mathematics, physics, or engineering, proficiency in programming languages like Python or MATLAB, and often a relevant advanced degree (MS or PhD). Expertise with simulation software (e.g., COMSOL, ANSYS), high-performance computing systems, and familiarity with version control tools are commonly required. Strong analytical thinking, creativity, and effective communication skills help facilitate collaboration and the translation of complex models to actionable insights. These abilities are essential for accurately developing, validating, and interpreting models that drive data-driven decision-making in research and industry.

Is CS full of math?

Computational Modeling Scientists often use advanced mathematics, including calculus, linear algebra, and statistics, to develop and analyze models. Strong math skills are essential for understanding algorithms, data analysis, and simulation techniques in this field.

What is meant by computational thinking?

Computational thinking is a problem-solving approach used by computational modeling scientists that involves breaking down complex problems into manageable parts, recognizing patterns, abstracting key information, and developing algorithms. It is a fundamental skill for designing models, analyzing data, and creating simulations using programming languages and software tools.

What is an example of computation?

In the context of a Computational Modeling Scientist, an example of computation is performing mathematical calculations or simulations using algorithms and software to analyze complex systems. This often involves programming skills and tools like MATLAB, Python, or specialized modeling software to process data and generate models. Computation enables scientists to predict behaviors and test hypotheses in various scientific fields.

What is a Computational Modeling Scientist job?

A Computational Modeling Scientist uses mathematical models, simulations, and computational techniques to analyze complex systems and predict behaviors across various fields, such as physics, biology, engineering, and finance. They develop algorithms, implement numerical methods, and work with large datasets to extract insights. Their role often involves programming, data analysis, and collaboration with researchers to optimize designs or solve scientific and engineering challenges.

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Computational Modeling Scientist jobs near you
Infographic showing various Computational Modeling Scientist job openings in the United States as of June 2026, with employment types broken down into 1% Internship, 70% Full Time, 28% Part Time, and 1% Contract. Highlights an 85% Physical, 3% Hybrid, and 12% Remote job distribution, with an average salary of $111,343 per year, or $53.5 per hour.

Computational Theoretical Chemist II

1910

Boston, MA • On-site

Full-time

PTO

Posted yesterday

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
  • 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
  • 2 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

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