Quantum Life Sciences Chemist

Quantum Life Sciences Chemist

Requirements

• Ph.D. in computational chemistry, biophysics, bioinformatics, or a closely related field, with a strong focus on computational methodology development, and 0 to 6 years of post-PhD (postdoctoral or industrial) experience.
• Hands-on experience with modeling and simulation of biological systems, such as protein-ligand interactions, enzymatic reactions, or biomolecular dynamics.
• Enthusiasm for working in a collaborative, interdisciplinary, and dynamic team environment.
• Expert-level Python coding skills with experience in scientific libraries relevant to life sciences.
• Proven ability to stay updated on recent academic literature and trends in computational chemistry and biomolecular modeling.

Responsibilities

• Conduct innovative research, literature analysis, problem solving, and quantum workflow design in the areas of quantum-informed biomolecular modeling, drug discovery, and computational chemistry.
• Collaborate with quantum algorithm experts to identify areas where quantum computing can have the greatest impact in computational chemistry, biology, and life sciences.
• Contribute expertise in conventional (non-quantum-computing) algorithms to the development of in-house quantum algorithms. Serve as a technical lead in customer projects by collaborating with customers’ teams to integrate quantum computing-produced computational outputs into conventional life sciences workflows.
• Serve as a liaison between partner teams and PsiQuantum’s quantum information experts for innovative algorithm selection, development, and prioritization relevant to life sciences.
• Develop computational workflows that combine best-in-class conventional approaches (e.g., through high-performance computing (HPC)) with the breakthrough computational abilities of FTQC to reshape how quantum workflows are designed for life sciences applications.
• Serve as a subject matter expert in computational quantum chemistry and biomolecular modeling for PsiQuantum’s Quantum Solutions team, staying updated on recent academic literature, trends, and tools in life sciences.
• Foster collaboration across teams to maximize the impact of quantum algorithms and quantum computing-generated data in life sciences applications.
• Help shape external-facing materials that champion the applications of FTQC in the pharmaceutical, biotechnology, and life sciences industries (for key opinion leaders, media, and partners).
• Build and maintain external partnerships and collaborations on the topic, which can include meetings, group problem-solving sessions, or drafting research proposals, among others.
• Create organized internal reports and thoroughly document progress on assigned tasks.

Preferred Qualifications

• Strong foundational knowledge of quantum chemistry methods (e.g., DFT, coupled cluster theory, or wavefunction-based approaches) and molecular simulation techniques as applied to biomolecular systems.
• Experience with free energy perturbation (FEP), molecular docking, or similar computational techniques for drug discovery.
• Experience with machine learning (ML) techniques in computational drug discovery, biomolecular modeling, or structural biology.
• Experience with coding GPU-accelerated molecular simulations.
• Familiarity with hybrid quantum-classical methodologies, such as QM/MM, applied to biomolecular systems.
• Knowledge of quantum embedding theories (e.g., DMET, embedded correlated wavefunctions) and their application to large, complex biomolecular systems.
• Hands-on experience with quantum computing or quantum algorithms, especially as applied to biological or chemical systems.
• General understanding of light-matter interactions or electronic excitations relevant to biological or chemical systems, such as energy transfer or photochemical processes.
• Familiarity with advanced quantum mechanical methods (e.g., CASCI, CASSCF) and their relevance to modeling enzymatic reactions or metal-containing biomolecules.
• Demonstrated scientific communication skills through peer-reviewed publications, conference presentations, or collaboration with industry partners.
• Expert-level C++ or Fortran coding skills.