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 impactful drug discovery ...
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 impactful drug discovery ...
About the Role We are seeking a ML & Molecular Simulation Scientist to develop and apply methods at the intersection of 3D molecular simulation and machine learning, and see those methods through to ...
About the Role We are seeking a ML & Molecular Simulation Scientist to develop and apply methods at the intersection of 3D molecular simulation and machine learning, and see those methods through to ...
... with molecular dynamics simulation concepts (force fields, electrostatics, neighbor lists, periodic boundary conditions) sufficient to engage credibly with both colleagues and the MD simulator ...
... with molecular dynamics simulation concepts (force fields, electrostatics, neighbor lists, periodic boundary conditions) sufficient to engage credibly with both colleagues and the MD simulator ...
Familiarity with molecular dynamics simulation concepts (force fields, electrostatics, neighbor lists, periodic boundary conditions) sufficient to engage credibly with both colleagues and the MD ...
Familiarity with molecular dynamics simulation concepts (force fields, electrostatics, neighbor lists, periodic boundary conditions) sufficient to engage credibly with both colleagues and the MD ...
Familiarity with molecular dynamics simulation concepts (force fields, electrostatics, neighbor lists, periodic boundary conditions) sufficient to engage credibly with both colleagues and the MD ...
Familiarity with molecular dynamics simulation concepts (force fields, electrostatics, neighbor lists, periodic boundary conditions) sufficient to engage credibly with both colleagues and the MD ...
The role sits at the intersection of computational biophysics, molecular simulation, and agentic platform design. You will work with computational scientists, research engineers, ML scientists, and ...
The role sits at the intersection of computational biophysics, molecular simulation, and agentic platform design. You will work with computational scientists, research engineers, ML scientists, and ...
Familiarity with molecular simulation methods (e.g., molecular dynamics, coarse-grained modeling ... and/or machine learning approaches, with interest in applying them to biological questions.
Familiarity with molecular simulation methods (e.g., molecular dynamics, coarse-grained modeling ... and/or machine learning approaches, with interest in applying them to biological questions.
Postdoctoral Fellow, Biochemistry & Molecular Bio
Galveston, TX · On-site
$46K - $62K/yr
Familiarity with molecular simulation methods (e.g., molecular dynamics, coarse-grained modeling ... and/or machine learning approaches, with interest in applying them to biological questions.
Postdoctoral Fellow, Biochemistry & Molecular Bio
Galveston, TX · On-site
$46K - $62K/yr
Familiarity with molecular simulation methods (e.g., molecular dynamics, coarse-grained modeling ... and/or machine learning approaches, with interest in applying them to biological questions.
Postdoctoral Fellow, Biochemistry & Molecular Bio
Galveston, TX · On-site
$46K - $62K/yr
Familiarity with molecular simulation methods (e.g., molecular dynamics, coarse-grained modeling ... and/or machine learning approaches, with interest in applying them to biological questions.
Postdoctoral Fellow, Biochemistry & Molecular Bio
Galveston, TX · On-site
$46K - $62K/yr
Familiarity with molecular simulation methods (e.g., molecular dynamics, coarse-grained modeling ... and/or machine learning approaches, with interest in applying them to biological questions.
Post Doctoral
Los Angeles, CA · On-site
$53K - $73K/yr
Experience with molecular simulation, machine learning, or related computational methods for molecular or materials systems. * Background in polymer science, soft materials, complex fluids, or ...
Post Doctoral
Los Angeles, CA · On-site
$53K - $73K/yr
Experience with molecular simulation, machine learning, or related computational methods for molecular or materials systems. * Background in polymer science, soft materials, complex fluids, or ...
Deep domain knowledge in at least one of: medicinal chemistry, cheminformatics, structural biology, molecular simulation, or computational drug discovery. * Excellent Python skills - you write clean ...
Deep domain knowledge in at least one of: medicinal chemistry, cheminformatics, structural biology, molecular simulation, or computational drug discovery. * Excellent Python skills - you write clean ...
Postdoctoral researcher in AI-driven Molecular Design
Los Alamos, NM · On-site
$44K - $60K/yr
Implement high-throughput workflows for molecular property prediction and simulation * Publish results in high-impact peer-reviewed journals and present at national/international conferences The ...
Postdoctoral researcher in AI-driven Molecular Design
Los Alamos, NM · On-site
$44K - $60K/yr
Implement high-throughput workflows for molecular property prediction and simulation * Publish results in high-impact peer-reviewed journals and present at national/international conferences The ...
Postdoctoral researcher in AI-driven Molecular Design
Los Alamos, NM · On-site +1
$44K - $60K/yr
Implement high-throughput workflows for molecular property prediction and simulation * Publish results in high-impact peer-reviewed journals and present at national/international conferences The ...
Postdoctoral researcher in AI-driven Molecular Design
Los Alamos, NM · On-site +1
$44K - $60K/yr
Implement high-throughput workflows for molecular property prediction and simulation * Publish results in high-impact peer-reviewed journals and present at national/international conferences The ...
CADD / Application Scientist
New York, NY · On-site
$164K - $259K/yr
We are developing physics-grounded models for molecular simulation that can make the chemical and biological systems behind drug discovery more learnable, predictable, and designable. You will be ...
CADD / Application Scientist
New York, NY · On-site
$164K - $259K/yr
We are developing physics-grounded models for molecular simulation that can make the chemical and biological systems behind drug discovery more learnable, predictable, and designable. You will be ...
Post Doctoral
$45K - $61K/yr
Experience with molecular simulation, machine learning, or related computational methods for molecular or materials systems Background in polymer science, soft materials, complex fluids, or related ...
Post Doctoral
$45K - $61K/yr
Experience with molecular simulation, machine learning, or related computational methods for molecular or materials systems Background in polymer science, soft materials, complex fluids, or related ...
CADD, Application Scientist
Manhattan, NY · On-site
We are developing physics-grounded models for molecular simulation that can make the chemical and biological systems behind drug discovery more learnable, predictable, and designable. You will be ...
CADD, Application Scientist
Manhattan, NY · On-site
We are developing physics-grounded models for molecular simulation that can make the chemical and biological systems behind drug discovery more learnable, predictable, and designable. You will be ...
Computational Chemistry / Theory Consultant
Emeryville, CA · Remote
$150 - $200/hr
Position Summary The Astera Institute is seeking a Computational Chemistry / Theory Consultant to provide the specialist molecular-simulation and theory for a nanoscale electrostatic actuator -- the ...
Quick apply
Computational Chemistry / Theory Consultant
Emeryville, CA · Remote
$150 - $200/hr
Position Summary The Astera Institute is seeking a Computational Chemistry / Theory Consultant to provide the specialist molecular-simulation and theory for a nanoscale electrostatic actuator -- the ...
Staff Research Engineer, Scientific Computing and ML/Physics Infrastructure
Cambridge, MA · On-site
$224K - $294K/yr
Build and support ML and physics infrastructure for model training, molecular simulation, data processing, and agent-executed scientific workflows. * Ensure workflows run reliably across multiple ...
Staff Research Engineer, Scientific Computing and ML/Physics Infrastructure
Cambridge, MA · On-site
$224K - $294K/yr
Build and support ML and physics infrastructure for model training, molecular simulation, data processing, and agent-executed scientific workflows. * Ensure workflows run reliably across multiple ...
PsiThera is seeking a consultant computational medicinal chemist with expertise in drug discovery, molecular simulations and AI/ML to join our dynamic, multidisciplinary team. Our science, our team ...
New
Quick apply
PsiThera is seeking a consultant computational medicinal chemist with expertise in drug discovery, molecular simulations and AI/ML to join our dynamic, multidisciplinary team. Our science, our team ...
New
Preferred Qualifications Equipment Utilized AMBER, OpenMM, and GROMACS simulation packages, relevant molecular simulation analysis tools, Python programming language, and GitLab environment. Physical ...
Preferred Qualifications Equipment Utilized AMBER, OpenMM, and GROMACS simulation packages, relevant molecular simulation analysis tools, Python programming language, and GitLab environment. Physical ...
Molecular Simulation information
See salary details
$11K - $19.4K
0% of jobs
$19.4K - $27.8K
0% of jobs
$27.8K - $36.2K
0% of jobs
$36.2K - $44.6K
0% of jobs
$44.6K - $53K
0% of jobs
$53K - $61.5K
0% of jobs
$65.5K is the 25th percentile. Wages below this are outliers.
$61.5K - $69.9K
52% of jobs
$69.9K - $78.3K
15% of jobs
$78.3K - $86.7K
0% of jobs
$86.7K - $95.1K
1% of jobs
$96.9K is the 75th percentile. Wages above this are outliers.
$95.1K - $103.5K
32% of jobs
$11K
$80.7K
$103.5K
How much do molecular simulation jobs pay per year?
As of Aug 6, 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 molecular simulation?
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?
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?
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.
More about Molecular Simulation jobs
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What are the most commonly searched types of Molecular Simulation jobs? The most popular types of Molecular Simulation jobs are:
What states have the most Molecular Simulation jobs? States with the most job openings for Molecular Simulation jobs include:
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Full-time
Re-posted 25 days ago
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 impactful 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.
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 impactful 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.