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 ...
Post Doctoral
$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
$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 ...
Structural biology and molecular simulation outputs. * Collaborate with Research Scientists. * Partner with medicinal chemists to support compound design and lead optimization. * Work with biologists ...
Structural biology and molecular simulation outputs. * Collaborate with Research Scientists. * Partner with medicinal chemists to support compound design and lead optimization. * Work with biologists ...
Use structural modeling and simulation tools, including AlphaFold 3, Rosetta, and molecular dynamics simulations, to investigate protein structures, conformational stability, molecular interactions ...
Use structural modeling and simulation tools, including AlphaFold 3, Rosetta, and molecular dynamics simulations, to investigate protein structures, conformational stability, molecular interactions ...
Research Associate, Computational Protein Engineering (Contract)
Tustin, CA · On-site
$75K - $85K/yr
Use structural modeling and simulation tools, including AlphaFold 3, Rosetta, and molecular dynamics simulations, to investigate protein structures, conformational stability, molecular interactions ...
Research Associate, Computational Protein Engineering (Contract)
Tustin, CA · On-site
$75K - $85K/yr
Use structural modeling and simulation tools, including AlphaFold 3, Rosetta, and molecular dynamics simulations, to investigate protein structures, conformational stability, molecular interactions ...
Use structural modeling and simulation tools, including AlphaFold 3, Rosetta, and molecular dynamics simulations, to investigate protein structures, conformational stability, molecular interactions ...
Use structural modeling and simulation tools, including AlphaFold 3, Rosetta, and molecular dynamics simulations, to investigate protein structures, conformational stability, molecular interactions ...
Senior Machine Learning Scientist I, Drug Discovery Analytics
Redwood City, CA · Hybrid
$112K - $153K/yr
Structural biology and molecular simulation outputs. * Collaborate with Research Scientists. * Partner with medicinal chemists to support compound design and lead optimization. * Work with biologists ...
Senior Machine Learning Scientist I, Drug Discovery Analytics
Redwood City, CA · Hybrid
$112K - $153K/yr
Structural biology and molecular simulation outputs. * Collaborate with Research Scientists. * Partner with medicinal chemists to support compound design and lead optimization. * Work with biologists ...
Structural biology and molecular simulation outputs. Required Skills, Experience and Education: * PhD in machine learning, computational chemistry, computational biology, computer science, or a ...
Structural biology and molecular simulation outputs. Required Skills, Experience and Education: * PhD in machine learning, computational chemistry, computational biology, computer science, or a ...
Principal Scientist (Computational Chemistry)
South San Francisco, CA · On-site +1
$144K - $269K/yr
Deep knowledge of computational chemistry principles and general molecular modeling techniques (e.g., docking, molecular simulation and dynamics, quantum mechanics, ligand- and structure-based design)
Principal Scientist (Computational Chemistry)
South San Francisco, CA · On-site +1
$144K - $269K/yr
Deep knowledge of computational chemistry principles and general molecular modeling techniques (e.g., docking, molecular simulation and dynamics, quantum mechanics, ligand- and structure-based design)
Principal Scientist (Computational Chemistry)
South San Francisco, CA · On-site
$144K - $269K/yr
Deep knowledge of computational chemistry principles and general molecular modeling techniques (e.g., docking, molecular simulation and dynamics, quantum mechanics, ligand- and structure-based design)
Principal Scientist (Computational Chemistry)
South San Francisco, CA · On-site
$144K - $269K/yr
Deep knowledge of computational chemistry principles and general molecular modeling techniques (e.g., docking, molecular simulation and dynamics, quantum mechanics, ligand- and structure-based design)
... molecular simulation, drug discovery, biomedical imaging, or biomedical foundation models. • Strong proficiency in AI methods relevant to life sciences, including protein language models, sequence ...
... molecular simulation, drug discovery, biomedical imaging, or biomedical foundation models. • Strong proficiency in AI methods relevant to life sciences, including protein language models, sequence ...
Systems Engineer - Simulation Correctness
Palo Alto, CA · On-site
$190K - $250K/yr
Increase simulation throughput by two orders of magnitude * Expand simulation capabilities to ... FEM, FEA, Molecular Dynamics, FDTD * Experience as a systems engineer in a production environment ...
Systems Engineer - Simulation Correctness
Palo Alto, CA · On-site
$190K - $250K/yr
Increase simulation throughput by two orders of magnitude * Expand simulation capabilities to ... FEM, FEA, Molecular Dynamics, FDTD * Experience as a systems engineer in a production environment ...
Familiarity with at least one domain: computational chemistry, molecular simulation, or materials informatics Preferred Qualifications: * Experience building multi-agent or LLM-orchestrated systems ...
Familiarity with at least one domain: computational chemistry, molecular simulation, or materials informatics Preferred Qualifications: * Experience building multi-agent or LLM-orchestrated systems ...
Software Engineer - Core Infrastructure
San Mateo, CA · On-site
$197K - $233K/yr
Genesis Molecular AI is building a world-class computational team to solve problems in drug discovery through machine learning, biophysical simulation, and computational chemistry. We are looking for ...
Software Engineer - Core Infrastructure
San Mateo, CA · On-site
$197K - $233K/yr
Genesis Molecular AI is building a world-class computational team to solve problems in drug discovery through machine learning, biophysical simulation, and computational chemistry. We are looking for ...
ML Engineer, Biological Analysis & Simulation
San Francisco, CA · On-site
$150K - $200K/yr
You will also integrate and experiment with simulation tools for small molecule discovery, such as ADMET prediction, docking scoring, Boltzmann generators and related computational chemistry engines.
Quick apply
ML Engineer, Biological Analysis & Simulation
San Francisco, CA · On-site
$150K - $200K/yr
You will also integrate and experiment with simulation tools for small molecule discovery, such as ADMET prediction, docking scoring, Boltzmann generators and related computational chemistry engines.
Principal Computational Scientist, Discovery Chemistry
South San Francisco, CA · On-site +1
$144K - $269K/yr
Deep knowledge of computational chemistry principles and general molecular modeling techniques (e.g., docking, molecular simulation, homology modeling, quantum mechanics, ligand- and structure-based ...
Principal Computational Scientist, Discovery Chemistry
South San Francisco, CA · On-site +1
$144K - $269K/yr
Deep knowledge of computational chemistry principles and general molecular modeling techniques (e.g., docking, molecular simulation, homology modeling, quantum mechanics, ligand- and structure-based ...
Molecular Simulation information
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.
What are popular job titles related to Molecular Simulation jobs in California? For Molecular Simulation jobs in California, the most frequently searched job titles are:
What job categories do people searching Molecular Simulation jobs in California look for? The top searched job categories for Molecular Simulation jobs in California are:
What cities in California are hiring for Molecular Simulation jobs? Cities in California with the most Molecular Simulation job openings:
Full-time
Re-posted 21 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.