PsiQuantum is looking to revolutionize chemistry and materials science through quantum computing and advanced machine learning.
Requirements
Ph.D. in cheminformatics, computational chemistry or physics, chemical or materials engineering, or closely related fields, with a strong focus on ML methodologies for molecular modeling or materials discovery.
Hands-on experience developing and applying machine learning models to solve real-world problems in cheminformatics, drug design, or materials science.
Expertise in Python programming and familiarity with scientific libraries and ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
Demonstrated ability to develop computational workflows integrating ML and molecular modeling tools.
Published peer-reviewed articles in the field of molecular modeling, applied machine learning, or cheminformatics.
Experience with molecular modeling techniques, including quantum chemistry methods (e.g., DFT, coupled cluster theory, or wavefunction-based methods), molecular dynamics, or machine learning potentials.
Familiarity with techniques for property prediction, structure-to-function modeling, or molecular fingerprint generation.
Responsibilities
Conduct innovative research and develop workflows that combine quantum computing and ML-driven cheminformatics for molecular modeling and property prediction.
Develop and apply machine learning models to accelerate molecular and materials discovery in areas such as drug design, catalysis, and energy materials.
Collaborate with quantum algorithm experts to identify areas where quantum computing can have the greatest impact in cheminformatics and materials discovery.
Act as a technical lead in collaborative projects, working with internal and external teams to integrate quantum and ML-driven insights into cheminformatics workflows.
Serve as a subject matter expert in ML-driven cheminformatics, staying updated on recent advancements in AI, computational chemistry, and quantum computing.
Document and communicate research findings through internal reports, peer-reviewed publications, and conference presentations.
Other
0 to 6 years of post-PhD (postdoctoral or industrial) experience.
Equal employment opportunity for all applicants and employees.
