Senior Principal Research Scientist, Computational Chemistry

IDEAYA Biosciences•South San Francisco, CA

2d•$196,000 - $242,000•Onsite

About The Position

IDEAYA is a precision medicine oncology company committed to the discovery, development, and commercialization of transformative therapies for cancer. Our approach integrates expertise in small-molecule drug discovery, structural biology and bioinformatics with robust internal capabilities in identifying and validating translational biomarkers to develop tailored, potentially first-in-class targeted therapies aligned to the genetic drivers of disease. We have built a deep pipeline of product candidates focused on synthetic lethality and antibody-drug conjugates, or ADCs, for molecularly defined solid tumor indications. Our mission is to bring forth the next wave of precision oncology therapies that are more selective, more effective, and deeply personalized with the goal of altering the course of disease and improving clinical outcomes for patients with cancer. When you're at IDEAYA, you will be in the midst of brilliant minds working on precision medicine therapies to help cancer patients. We are passionate and committed about being on the forefront of oncology medicine, which means we all have a high internal drive that is at the very core of every person at IDEAYA. We are inquisitive, ask deep questions, and are data-driven innovators who like to collaborate and use team work to move science forward. For more information, please see www.ideayabio.com. We are seeking an accomplished Senior Principal Research Scientist in Computational Chemistry with significant pharmaceutical industry experience to join our multidisciplinary small molecule drug discovery organization. This is a senior individual contributor role for a highly experienced computational chemist with a strong track record of advancing pharmaceutical discovery programs through hands-on scientific impact. The successful candidate will support discovery project teams across target identification, hit discovery, lead optimization, and drug candidate selection. The role requires a high degree of independence, technical depth, and scientific judgment. The candidate will apply modern computational chemistry approaches to directly inform medicinal chemistry design and project decision-making. We are looking for a creative, detail-oriented scientist with a passion for drug discovery and a collaborative mindset. As part of the drug discovery team, the candidate will contribute directly to target assessment and druggability analysis, perform virtual screening and structure-based modeling, and work closely with medicinal chemists to design compounds with improved potency, selectivity, functional activity, and developability (e.g., ADME/DMPK). In addition to hands-on contributions, the candidate will mentor other scientists and share best practices to amplify the impact of computational chemistry across project teams. This position is based in our South San Francisco headquarter office and required to be onsite four days per week per our company policy.

Requirements

PhD in Computational Chemistry or a related discipline with 9+ years of pharmaceutical or biotechnology industry experience
Strong understanding of small molecule drug discovery and medicinal chemistry principles
Demonstrated expertise in structure-, ligand-, and fragment-based drug discovery
Expertise in free energy perturbation, molecular dynamics, quantum mechanics, cheminformatics, and ligand affinity estimation methods
Proven ability to independently deliver computational work that influences medicinal chemistry decisions and project outcomes
Ability to manage priorities across multiple discovery programs
Excellent oral and written communication skills
Experience applying machine learning or AI methods to molecular design, property prediction, or compound prioritization
Experience with Schrödinger modeling software and others (e.g., MOE, OpenEye)
Programming, scripting, statistics, and data analysis experience applied to drug discovery
Experience working on challenging target classes, including protein–protein interactions and allosteric pockets
Track record of contributing to discovery programs that advance high-quality small molecule drug candidates
All employees are expected to act with integrity and in full compliance with applicable laws, regulations, and IDEAYA policies, including IDEAYA’s Code of Conduct. Employees must demonstrate good judgement and ethical behavior in all business activities, maintain patient and product safety as a top priority, and report any suspected violations of law or Company policy through appropriate channels
This position requires you to be fully vaccinated from COVID-19, subject to reasonable accommodations for medical or religious reasons, and/or as otherwise required by applicable law. The Company considers you fully vaccinated once 14 days have passed since you received either the second dose in a two-dose COVID-19 vaccine series or a single-dose COVID-19 vaccine. The vaccine must have been FDA approved, have emergency use authorization from the FDA, or, for persons fully vaccinated outside of the U.S., be listed for emergency use by the World Health Organization.

Responsibilities

Lead structure-based drug design meetings with medicinal chemists and provide senior-level, hands-on drug design and computational chemistry support to small molecule drug discovery project teams
Contribute to programs from target identification through lead optimization and drug candidate selection
Apply structure-, ligand-, and fragment-based modeling to guide medicinal chemistry design
Use molecular dynamics, free energy methods, quantum chemistry, and cheminformatics to address complex design and prioritization questions
Translate computational analyses into clear, actionable compound design recommendations
Serve as a highly experienced computational contributor and scientific advisor within project teams
Mentor and coach other scientists in structure-based drug design through technical guidance and scientific discussion
Evaluate new computational methods, tools, and workflows and apply them when they add clear value
Maintain scientific rigor, reproducibility, and best practices in an industry drug discovery environment