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Molecular Simulation Jobs (NOW HIRING)

Xenon7

Research Advisor, Computational Chemistry

Perform molecular dynamics simulations of chemically modified oligonucleotide duplexes and single-stranded species to characterize the structural and thermodynamic consequences of sugar, backbone ...

ChampionX

Chemical Data Scientist

Sugar Land, TX · On-site

Proficiency with molecular simulation software (examples like Biovia Materials Studio). * Strong foundation in computational chemistry: DFT, MD, Monte Carlo. * Force field selection/parameterization;

ChampionX

Chemical Data Scientist

Sugar Land, TX · On-site

Proficiency with molecular simulation software (examples like Biovia Materials Studio). * Strong foundation in computational chemistry: DFT, MD, Monte Carlo. * Force field selection/parameterization;

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How much do molecular simulation jobs pay per year?

As of Jun 26, 2026, the average yearly pay for molecular simulation in the United States is $80,687.00, according to ZipRecruiter salary data. Most workers in this role earn between $69,000.00 and $98,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Molecular Simulation position, and why are they important?

To thrive in Molecular Simulation, you need a solid background in chemistry, physics, or computational science, often at the graduate level, with expertise in molecular modeling and statistical mechanics. Familiarity with industry-standard simulation software (such as GROMACS, AMBER, or CHARMM), programming languages (like Python or C++), and high-performance computing platforms is essential. Strong analytical thinking, attention to detail, and effective communication are valuable soft skills in this role. These competencies are crucial for accurately modeling molecular systems, interpreting results, and collaborating with multidisciplinary teams in research or industry settings.

What is a Molecular Simulation job?

A Molecular Simulation job involves using computational techniques to model and analyze molecular systems at the atomic level. Professionals in this field apply physics-based algorithms and software to study material properties, chemical reactions, and biological processes. They work in industries such as pharmaceuticals, materials science, and energy to optimize product development and research. Strong skills in computational chemistry, physics, and programming are essential for this role.

What are some common challenges faced by professionals in molecular simulation roles?

Professionals in molecular simulation often encounter challenges such as optimizing computational workloads, troubleshooting simulation errors, and interpreting complex data outputs. Balancing the accuracy of simulations with computational efficiency can also be demanding, especially when working with large biomolecular systems or advanced algorithms. Additionally, staying abreast of rapidly evolving software tools and scientific methodologies requires ongoing learning and adaptation. Being able to collaborate with experimental scientists and clearly communicate results is important for integrating simulation findings into broader research projects.

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Molecular Simulation jobs near you
Infographic showing various Molecular Simulation job openings in the United States as of June 2026, with employment types broken down into 61% Full Time, 34% Part Time, and 5% Contract. Highlights an 69% Physical, 1% Hybrid, and 30% Remote job distribution, with an average salary of $80,687 per year, or $38.8 per hour.

ML & Molecular Simulation Scientist

Genesis Molecular AI

San Mateo, CA • On-site

Full-time

This job post has expired 2 days ago. Applications are no longer accepted.

Job description

Job Summary:
Genesis Molecular AI is pioneering foundation models for molecular AI to unlock a new era of drug design and development. They are seeking a ML & Molecular Simulation Scientist to develop and apply methods at the intersection of 3D molecular simulation and machine learning, contributing to drug discovery programs.
Responsibilities:
• Build and apply ML models informed by 3D structural data, including geometric deep learning, equivariant neural networks, and diffusion-based generative models for molecular design and property prediction
• Integrate physics-based and ML + data-driven approaches, combining force field methods, quantum chemistry, and structure-based design with modern ML to improve accuracy and throughput
• Develop and apply simulation methods spanning molecular dynamics, enhanced sampling (metadynamics, replica exchange, umbrella sampling), and free energy calculations (FEP/TI) to support active drug discovery programs
• Contribute to the GEMS platform, improving our generative AI and scoring capabilities, focusing on 3D methods; strengthen ML and physics-based scoring functions (and their intersection), build next-gen force fields
• Work directly with CADD and discovery scientists to apply computational methods across the drug discovery pipeline, from target structure analysis through lead optimization
• Stay current with the field, implementing and adapting methods from the latest literature in geometric ML, biomolecular simulation, and computational drug design
• Communicate scientific results clearly to multidisciplinary teams, including experimental chemists and biologists
Qualifications:
Required:
• Practical experience with 3D machine learning – geometric deep learning, graph neural networks, equivariant architectures (e.g., SE(3)/E(3) networks), or diffusion models applied to molecular data
• PhD (preferred) in computer science, machine learning, chemical engineering, biophysics, physics, or a closely related field; postdoctoral or industry experience is a plus
• Deep, hands-on expertise in molecular simulation, including MD, enhanced sampling, and/or free energy methods using tools such as GROMACS, AMBER, OpenMM, or NAMD
• Familiarity with structure-based drug design workflows: docking, binding site analysis, protein-ligand interaction modeling using tools such as MOE, or PyMOL
• Proficiency in Python and scientific computing libraries (PyTorch, JAX, NumPy, MDAnalysis, RDKit); comfort with HPC environments and scripting for large-scale simulation workflows
• A track record of applying computational methods to real scientific problems, demonstrated through publications, open-source contributions, or industry impact
• Collaborative, curious, and able to move between rigorous method development and fast-paced discovery work
Preferred:
• Familiarity with cheminformatics and ADMET property prediction
• Contributions to open-source simulation or ML tooling
Company:
Genesis Therapeutics unifies AI and biotech to accelerate the discovery of new medicines. Founded in 2019, the company is headquartered in South San Francisco, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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