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Eli Lilly and Company Research Scientist-Medicinal/Computational Chemist - R-9499 in Indianapolis, Indiana

At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our 39,000 employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. Were looking for people who are determined to make life better for people around the world.For more than 140 years, Eli Lilly has been dedicated to meeting the health care needs of people around the world. We address these needs primarily by developing innovative medicinesinvesting a percentage of our sales in research and development in the top tier for major pharmaceutical companies. Lilly credits its exceptional employees for its success, and furthermore recognizes that the key to ongoing achievement lies in attracting and retaining the best people. A company rich in heritage, Lilly employs individuals, conducts research and markets products worldwide.The Medicines Innovation Hub within Lilly Research Laboratories is seeking a highly skilled Drug Discovery Scientist and teammate to join the Computational Chemistry and Informatics group. Do you have strong synthetic organic chemistry skills with deep and extensive working knowledge of modern synthetic chemistry methodologies, experimental work, isolation/purification techniques and structural analysis of synthetic organic molecules? If you also have knowledge in computational techniques to craft molecules we want you on our team! We are an innovative and dynamic company looking to enhance our diverse capabilities in drug discovery. We are committed to continually improving our abilities to make life better for patients around the world.Lilly is a top Pharmaceutical company with employees dedicated to the patients, families and communities we serve. Come be part of our team!Keep safety as a top priority at any time, striving to maintain a strong safety culture.Formulate hypothesis and design novel small molecules to engage disease modifying targets and contribute critically to the advancement of drug discovery programs from early lead generation to submission of candidate drugs to the clinic.Support de-novo molecular design through computational chemistry, structure-based drug design and ligand-identification technologies to characterize protein-ligand interactions to gain key insightsDesign optimized lead compounds to improve potency, selectivity, physicochemical properties and DMPK to meet the target product profiles required to invent high-quality medicines.Lead and manage discovery projects across disease areas using CRO and/or in-house and/or resources leading to preclinical candidates for further clinical development. Manage high laboratory synthetic productivity to inform fast-paced SAR iterations through proposal and execution of synthetic routes.Collaborate with colleagues specialized in high-throughput automated synthesis, route optimization and scale-up to maximize the overall efficiency and productivity of the group.Collaborate with scientists across functional areas like pharmacology, translational science, ADME and toxicology to address program needs, increase your business acuity and provide them with Medicinal Chemistry perspectives.Basic qualificationsPhD in Organic Chemistry, Computational Chemistry, Informatics or related fieldAt least 2 years of experience in small molecule organic synthesis and synthetic methodology, either in pharmaceutical industry or postdoctoral experience.Additional skills/preferencesExperience using state-of-the-art Computational Chemistry software and algorithms to craft and optimize small molecule drug targets.Maintain awareness of latest literature of chemical transformations.Scientific creativity and ability to work independently solving problems through careful experiment

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