Director / Sr. Director of Computational Chemistry for Molecule Discovery – ExploR&D
hace 10 días
Windlesham
At Lilly, the work is demanding because patients are waiting. We unite caring with discovery to help make life better for people around the world, knowing that every decision, every detail, and every day matters. Headquartered in Indianapolis, Indiana, our over 50,000 employees around the globe take on complex challenges to discover and deliver life‑changing medicines, strengthen how health is understood and managed, and support the communities we serve. This is hard, urgent, selfless work—but it’s work worth doing. If you’re driven by purpose and ready to bring your best to work that truly matters for patients, we invite you to join us. At Lilly, we serve an extraordinary purpose. We make a difference for people around the globe by discovering, developing, and delivering medicines that help them live longer, healthier, more active lives. Lilly Catalyze360 is a comprehensive approach to enabling the early‑stage biotech ecosystem by democratizing access to infrastructure, expertise, and resources. Through its interconnected pillars — Lilly Ventures, Lilly Gateway Labs, Lilly ExploR&D, and Lilly TuneLab — Catalyze360 strategically removes barriers that traditionally block bold science from becoming life‑changing medicines, providing biotechs with flexible combinations of capital, physical lab space, R&D capabilities, AI/ML tools, and decades of enterprise learning. Lilly ExploR&D is a team of drug discovery and development experts who partner with biotechs from discovery through clinical proof‑of‑concept, putting Lilly’s industry‑leading capabilities behind their missions. We provide flexible support — from strategic consulting to full program execution — making it faster, easier, and more capital‑efficient for innovators to transform bold science into life‑changing medicines. The Lilly Small Molecule Discovery group (LSMD) is an internal research organization dedicated to creating molecules that make life better for people. LSMD applies cutting‑edge science to unlock new small‑molecule approaches for diseases with limited treatment options. Both Lilly ExploR&D and LSMD are committed to discovering innovative molecules that deliver breakthrough efficacy with the strongest possible safety margins. Their success in external and internal innovation is grounded in a culture of scientific excellence, open collaboration, creative problem solving, and individual accountability. ExploR&D’s Molecule Discovery Team is expanding its capabilities to partner with small‑molecule biotechs at any stage of discovery. To support this effort, the team works closely with Lilly’s LSMD organization and draws on its technical expertise in small‑molecule hit‑to‑lead and lead optimization, including the application of state‑of‑the‑art computational chemistry technologies across innovative targets. We seek an expert computational chemist with a proven record of applying in silico technologies to discover high‑quality hit and lead molecules for difficult‑to‑drug therapeutic targets. This lead‑from‑the‑bench role requires a dynamic, versatile, hands‑on scientist who can quickly adapt to each biotech partner and help advance novel targets and therapeutic hypotheses, regardless of the stage or complexity of the discovery campaign. In close partnership with the LSMD Early Molecular Discovery Computational Chemistry and Cheminformatics team, the ExploR&D Computational Chemist will apply virtual screening, cheminformatics, and AI/ML technologies to support screening library design, hit identification/modeling, and virtual hit expansion toward novel, efficacious lead molecules. The candidate will also conduct advanced generative and structure‑based molecular design and fully leverage the TuneLab drug discovery AI/ML platform and its predictive models. This highly collaborative role requires seamless engagement with Lilly cross‑functional partners to create data‑driven design hypotheses and models while collaborating to accelerate biotech molecule discovery. Success in this position requires excellent interpersonal skills, a positive can‑do attitude, and the ability to thrive in a fluid, fast‑paced, and highly interactive team environment. • Lead from the bench by applying state‑of‑the‑art computational chemistry, virtual screening, cheminformatics, ML/AI, and advanced analytics to support target, ligand‑binding domain, and mechanism‑of‑action assessments; library design; hit identification; and hit‑to‑lead progression across multiple target classes and modalities., • Seamlessly engage with biotech teams, external medicinal chemists, biologists, and other internal and external partners to develop workflows that generate optimal screening collections, high‑quality models, and testable ligand‑design hypotheses, strengthening the ability of Biotech/ExploR&D collaboration teams to deliver differentiated hits and leads., • Support joint‑team success by guiding the application of modern cheminformatics and ML/AI methods to library design—including diversity, focused, bridging, fragment, and DEL collections—large‑data analysis, predictive active‑learning models, internal and external data mining, hit prioritization and expansion, and ligand‑ or fragment‑based design., • Proactively leverage emerging technologies that can accelerate prosecution of challenging targets and delivery of differentiated, high‑quality leads., • Cultivate cross‑area collaborations with TuneLab platform colleagues to guide and apply transformative approaches for predictive model development and hit and lead discovery., • Deliver timely, high‑quality data, rigorous analyses, and robust models to joint project teams to accelerate decisions on chemical series and project progression., • Demonstrate curiosity and learning agility by learning from and adapting to non‑small‑molecule modalities, such as antibodies and RNA therapeutics, with the medium‑to‑long‑term goal of expanding ExploR&D computational chemistry capabilities into these areas., • Provide strong scientific leadership and strategic guidance across all ExploR&D computational chemistry activities to drive data‑driven drug discovery., • PhD in Computational Chemistry, Cheminformatics, CompBiophysics or a related field, with at least 7 years of relevant research and/or industry experience (may include post‑doc experience), or MS with 10+ years industry/academic/research, or BS with 15+ years industry/academic/research experience., • Exceptional record of applying computational chemistry, virtual screening, and cheminformatics approaches to accelerate target assessment, hit identification and expansion, lead generation, and library design as exemplified through patent contributions and high‑impact publications., • Deep scientific expertise in physics‑based modeling and ligand‑ and structure‑based drug design., • Strong cheminformatics skills with experience in data analytics, AI/ML modeling and basics of statistical principles. Ability to build, sustain, and model a culture of innovation, collaboration, and commitment., • Demonstrated growth mindset and ability to collaborate effectively with computational chemistry leaders, while maintaining appropriate IP protections, to strengthen Lilly’s global computational chemistry capabilities., • Demonstrated ability to identify and champion new technologies that lead to successful drug discovery applications., • Strong scientific programming skills (Python essential)., • Proven ability to establish and drive effective collaborations with external biotech teams, including medicinal chemists and scientists from other disciplines, to achieve project goals and timelines., • Ability to communicate effectively with internal and external team members, cross‑functional colleagues, and senior leaders., • Innate curiosity, flexibility, and learning agility to address diverse drug discovery challenges, including novel targets, mechanisms, and therapeutic modalities., • Experience applying computational methods to RNA, antibody, or ADC research is not required but will be highly valued., • Strong understanding of drug discovery from target assessment through candidate selection, including core principles of drug design, medicinal chemistry, and ADME., • Proficiency with cheminformatics toolkits (e.g. RDKit, OpenEye), and machine learning libraries (e.g. PyTorch, scikit‑learn)., • Fluency with AI coding and research assistants (e.g. Claude Code)., • Ability to clearly communicate goals and priorities across computational chemistry teams., • Agile and prepared to adjust research priorities as needed to ensure success., • Proven ability to collaborate across disciplines to achieve project goals and timelines., • Ability to work independently while contributing effectively to a larger collaborative team., • Highly organized, with strong analytical, documentation, time‑management, and multitasking skills., • Views personal success as an outcome of team success., • Self‑driven, accountable, hardworking, and guided by data‑driven decision‑making. The physical demands of this job are consistent with a lab environment. The physical demands here are representative of those that must be met by an employee to successfully perform the essential functions of this job. There will be up to 20% travel associated with this role. This position’s work environment is in a Laboratory. The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job. • To perform this job successfully, an individual must be able to perform the role and responsibilities satisfactorily. The requirements listed above are representative of the knowledge, skill, and/or ability required. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions. Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form https://careers.lilly.com/us/en/workplace-accommodation for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response. Lilly is proud to be an EEO Employer and does not discriminate on the basis of age, race, color, religion, gender identity, sex, gender expression, sexual orientation, genetic information, ancestry, national origin, protected veteran status, disability, or any other legally protected status. Our employee resource groups (ERGs) offer strong support networks for their members and are open to all employees. Our current groups include: Africa, Middle East, Central Asia (AMECA), Black Employees at Lilly (BE@Lilly), Chinese Culture Network (CCN), EnAble, Evolve, Lilly Indian Network (LIN), Organization of Latinx at Lilly (OLA), Pride (LGBTQ+ Allies), Veterans Leadership Network (VLN) and Women’s Initiative for Leading at Lilly (WILL). Actual compensation will depend on a candidate’s education, experience, skills, and geographic location. The anticipated wage for this position is $193,500 - $338,800. Full‑time equivalent employees also will be eligible for a company bonus (depending, in part, on company and individual performance). In addition, Lilly offers a comprehensive benefit program to eligible employees, including eligibility to participate in a company‑sponsored 401(k); pension; vacation benefits; eligibility for medical, dental, vision and prescription drug benefits; flexible benefits (e.g., healthcare and/or dependent day care flexible spending accounts); life insurance and death benefits; certain time off and leave of absence benefits; and well‑being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities). Lilly reserves the right to amend, modify, or terminate its compensation and benefit programs in its sole discretion and Lilly’s compensation practices and guidelines will apply regarding the details of any promotion or transfer of Lilly employees. WeAreLilly #J-18808-Ljbffr
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