Remote | Quantum Chemistry & Electronic Structure Specialist — $60–$90/hour

24-Mag•New York, NY

3d•Remote

About The Position

We are sharing a specialised part-time consulting opportunity for computational chemistry professionals with deep expertise in quantum chemistry, electronic structure methods, scientific computing, and research-grade simulation workflows. This role supports the development of advanced AI benchmarks for research-level scientific problem solving. Selected experts will design original computational chemistry problems that require AI systems to use specialised scientific software, perform electronic structure calculations, interpret results, diagnose methodological limitations, and reason through complex multi-step workflows.

Requirements

Graduate-level expertise in Computational Chemistry, Quantum Chemistry, Chemical Physics, Theoretical Chemistry, or a closely related STEM discipline
MS, PhD, or equivalent substantial research experience
Strong hands-on experience with electronic structure calculations and quantum chemistry software
Proven proficiency with PySCF or comparable scientific computing platforms
Experience using Hartree-Fock, DFT, TDDFT, CASSCF, post-HF, or related methods in research or professional work
Strong Python programming skills
Deep understanding of method selection, electronic structure diagnostics, excited-state analysis, and computational artefacts
Ability to interpret difficult or ambiguous computational results
Comfortable working in Linux, terminal environments, and remote compute sandboxes
Experience demonstrated through research publications, open-source contributions, or professional computational work

Nice To Haves

Familiarity with benchmark design, scientific education, examination development, or problem-set creation is advantageous
Experience with computational reproducibility or containerised environments is highly valued

Responsibilities

Develop challenging computational problems involving quantum chemistry and electronic structure analysis
Create tasks using Hartree-Fock, DFT, TDDFT, CASSCF, post-HF, and related computational methods
Design scenarios requiring careful selection of appropriate electronic structure methods
Evaluate orbital behaviour, electronic states, energies, and wavefunction characteristics
Develop problems involving difficult or non-trivial electronic structures
Create computational tasks involving excited states and electronic transitions
Develop scenarios requiring interpretation of orbital populations, configurations, and diagnostics
Evaluate whether computational results are physically and chemically meaningful
Design problems involving competing electronic configurations or methodological ambiguity
Identify artefacts arising from approximations, convergence behaviour, or method limitations
Develop problem setups using PySCF or comparable quantum chemistry software
Write Python code supporting calculations, validation logic, and benchmark workflows
Create reproducible simulation environments for electronic structure calculations
Diagnose numerical, convergence, and implementation issues in computational workflows
Apply hands-on knowledge of scientific software limitations and edge cases
Design original graduate-level problems based on realistic computational chemistry workflows
Create tasks requiring multi-step scientific reasoning rather than straightforward calculation
Develop both fully specified simulation problems and information-recovery challenges
Construct problems where systems must determine which calculations or analyses to perform
Ensure tasks reward method selection, interpretation, and scientific judgement
Test problem designs against advanced AI systems
Evaluate whether tasks reach the intended level of technical and reasoning difficulty
Refine problems based on observed model performance
Develop oracle functions, solution validators, and reference calculations
Confirm that each problem is technically rigorous, reproducible, and sufficiently well defined
Design scenarios reflecting authentic research-level computational chemistry practice
Evaluate trade-offs between computational cost, numerical stability, and methodological accuracy
Analyse cases where multiple computational approaches appear plausible
Identify hidden assumptions or methodological limitations affecting conclusions
Produce reference solutions demonstrating expert-level scientific reasoning