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Research Advisor, Computational Chemistry

2 months, 3 weeks ago
India
Full-time
Senior
Research Scientist
Data Science and Analytics
Helm Machine Learning NumPy Python Rust SciPy
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Xenon7

Xenon7

Xenon7 provides advanced AI solutions and consultancy services, leveraging a team of highly qualified experts and a strong emphasis on research and innovation to address complex industry challenges and enhance operational efficiency.

Internet Software & Services
Founded 2014
View All Jobs 14

Description

  • Perform molecular dynamics simulations of chemically modified oligonucleotide duplexes and single‑stranded species to characterize structural and thermodynamic consequences of sugar, backbone, and base modifications.
  • Apply free energy methods (FEP, thermodynamic integration, MM/PBSA, MM/GBSA) to predict modification‑dependent binding affinities, duplex stability, and protein–oligonucleotide interactions.
  • Develop and validate force field parameters for novel nucleotide analogs using quantum mechanical calculations to enable rapid computational evaluation of new chemistries.
  • Build and apply cheminformatics descriptors and QSAR/QSPR models adapted for chemically modified oligonucleotides, moving beyond sequence‑only representations to capture full chemical diversity.
  • Collaborate with medicinal chemists and biologists to integrate computational predictions with experimental SAR data and contribute to identifying optimal modification patterns for potency, selectivity, metabolic stability, and safety.
  • Contribute to reusable computational workflows, data assets, and modeling platforms that support cross‑program learning and integration with the team’s unified machine learning models.
  • Present findings to cross‑functional teams and contribute to scientific strategy discussions, publications, and patent applications.
  • Bridge molecular simulation, cheminformatics, and machine learning to generate actionable insights that guide optimization across the RNA therapeutics portfolio.

Requirements

  • PhD in computational chemistry, physical chemistry, chemical physics, biophysics, or a closely related field.
  • Demonstrated expertise in molecular dynamics simulation of nucleic acids or chemically modified biopolymers.
  • Experience with free energy calculation methods applied to biomolecular systems (FEP, TI, MM/PBSA, MM/GBSA).
  • Proficiency with cheminformatics toolkits (RDKit, OpenEye) and/or commercial CADD platforms (Schrödinger, MOE).
  • Strong programming skills in Python with experience in scientific computing libraries.
  • Familiarity with machine learning and AI methods applied to molecular sciences, including predictive modeling for molecular properties, chemical optimization, or structure–activity relationships.
  • Experience with high‑performance computing and/or cloud‑based simulation environments.
  • Experience with force field parameterization for non‑standard nucleotide analogs, including QM‑derived charge fitting (RESP, AM1‑BCC) and torsion parameter development.
  • Familiarity with quantum chemical methods (DFT, ab initio) and molecular representations for modified oligonucleotides (HELM, extended SMILES, or similar).
  • Track record of peer‑reviewed publications demonstrating expertise in computational chemistry applied to nucleic acids or modified biopolymers and deep understanding of nucleic acid structure and common therapeutic modifications (2′‑OMe, 2′‑F, 2′‑MOE, LNA/cET, phosphorothioate, GalNAc conjugates).

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