Quantum Life Sciences Chemist

Description:

Are you eager to revolutionize life sciences using the transformative power of quantum computing? As a Quantum Life Sciences Chemist, you will lead efforts at the intersection of quantum computing, computational chemistry, and biology, solving critical challenges in drug design, biomolecular modeling, and biological systems simulation. By integrating quantum algorithms with established life sciences methodologies, you will pioneer new approaches to address complex problems in pharmaceuticals, biomaterials, and bioinformatics. Join our interdisciplinary team to advance quantum-enabled innovations and shape the future of life sciences.

At PsiQuantum’s Quantum Solutions team, your role will focus on bridging the gap between fault-tolerant quantum computing (FTQC) and established computational chemistry and life sciences tools. You will integrate these approaches with machine learning to explore novel workflows for quantum-informed drug discovery and biomolecular modeling. Your expertise in theoretical and computational chemistry will enable you to connect quantum-computed molecular insights with complex biological systems, driving advancements in drug design, biomaterials, and other critical areas within the life sciences.

This position requires a PhD in computational chemistry, biophysics, or a closely related field, preferably with postdoctoral research experience (although postdoc experience is not mandatory). We are looking for a curious, creative, and interdisciplinary thinker with a strong foundation in computational methodologies applicable to life sciences. The ideal candidate should be an avid reader of scientific literature, possess expert-level hands-on coding experience (e.g., Python, Fortran, C++), and have demonstrated skills in developing and applying computational techniques. Experience contributing to scientific software or modeling workflows is a plus. While prior knowledge of quantum information and fault-tolerant quantum computing is highly preferred, it is not required.

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.

Experience/Qualifications

Required:

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.

Preferred

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.