2 дня назад
Senior Principal Research Scientist, Computational Chemistry
196 000 - 242 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior Principal Research Scientist, Computational Chemistry (small-molecule drug discovery): Advancing pharmaceutical discovery programs from target identification through drug candidate selection with an accent on structure-based modeling, virtual screening, molecular dynamics, free energy methods, and medicinal chemistry collaboration. Focus on translating computational analyses into compound design decisions, addressing challenging protein targets, applying AI and machine learning to molecular design, and mentoring computational scientists.
Location: South San Francisco, California, United States; onsite four days per week
Salary: $196,000–$242,000 per year
Company
is a clinical-stage precision medicine oncology company developing targeted small-molecule therapies for molecularly defined cancer populations.
What you will do
- Lead structure-based drug design meetings and provide senior computational chemistry support to small-molecule discovery teams.
- Support programs from target identification and druggability assessment through hit discovery, lead optimization, and candidate selection.
- Apply structure-, ligand-, and fragment-based modeling, virtual screening, molecular dynamics, free energy methods, quantum chemistry, and cheminformatics.
- Translate computational analyses into actionable recommendations for compound potency, selectivity, functional activity, and developability.
- Serve as a scientific advisor, evaluate new computational workflows, and maintain rigorous and reproducible practices.
- Mentor and coach scientists in structure-based drug design and computational chemistry.
Requirements
- PhD in Computational Chemistry or a related discipline and 9+ years of pharmaceutical or biotechnology industry experience.
- Strong understanding of small-molecule drug discovery and medicinal chemistry principles.
- Expertise in structure-, ligand-, and fragment-based drug discovery, free energy perturbation, molecular dynamics, quantum mechanics, cheminformatics, and ligand affinity estimation.
- Experience with machine learning or AI for molecular design, property prediction, or compound prioritization.
- Experience with Schrödinger modeling software and tools such as MOE or OpenEye, plus programming, scripting, statistics, and data analysis.
- Experience with challenging target classes, including protein–protein interactions and allosteric pockets, and a track record of advancing small-molecule candidates.
Culture & Benefits
- Collaborative, inclusive, data-driven environment focused on precision oncology and improving outcomes for cancer patients.
- Medical, dental, and vision coverage, with 100% employee and 90% dependent coverage.
- 401(k), employee stock purchase plan, wellness programs, and potential merit increases, incentive compensation, and stock option awards.
- Work is performed onsite at the South San Francisco headquarters four days per week.
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