• Perform molecular dynamics simulations of chemically modified oligonucleotide duplexes and single‑stranded species to characterize the 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, enabling rapid computational evaluation of new chemistries emerging from the medicinal chemistry team • Build and apply cheminformatics descriptors and QSAR/QSPR models adapted for chemically modified oligonucleotides, moving beyond sequence‑only representations to capture the full chemical diversity of the modification space • Collaborate with medicinal chemists and biologists to integrate computational predictions with experimental SAR data, contributing to the identification of optimal modification patterns for on‑target 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

• Perform molecular dynamics simulations of chemically modified oligonucleotide duplexes and single‑stranded species to characterize the 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, enabling rapid computational evaluation of new chemistries emerging from the medicinal chemistry team • Build and apply cheminformatics descriptors and QSAR/QSPR models adapted for chemically modified oligonucleotides, moving beyond sequence‑only representations to capture the full chemical diversity of the modification space • Collaborate with medicinal chemists and biologists to integrate computational predictions with experimental SAR data, contributing to the identification of optimal modification patterns for on‑target 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

- Assist with customers' inquiries - Guide customers on their questions for the best use of the product/service - Maintain a high level of quality in each case you review

• Design and deliver high-quality, scalable Tableau dashboards aligned to business priorities • Translate stakeholder needs into structured analytics solutions and intuitive visual experiences • Act as a trusted advisor to business and leadership teams, shaping data-driven decisions • Champion data visualization best practices, design standards, and governance frameworks • Lead enablement efforts (training, mentorship, playbooks) to scale Tableau adoption • Partner with data teams to ensure robust data models, semantic consistency, and performance optimization