Senior Scientist Computational Chemistry. Nombre de la empresa: Johnson & Johnson. Ubicación de la empresa: Toledo (Castilla-La Mancha). Janssen Research & Development, L.L.C., a division of Johnson & Johnson's Family of Companies is recruiting for a Scientist or Senior Scientist in Computational Chemistry, located in Toledo, Spain. At the Janssen Pharmaceutical Companies of Johnson & Johnson, what matters most is helping people live full and healthy lives. We focus on treating, curing and preventing some of the most devastating and complex diseases of our time. And we pursue the most promising science, wherever it might be found. Janssen Research & Development, LLC discovers and develops innovative medical solutions to address important unmet medical needs in oncology, immunology, neuroscience, infectious diseases and vaccines, and cardiovascular and metabolic diseases. Please visit http://www.janssenrnd.com/ for more information. We are Janssen. Our mission drives us. Our patients inspire us. We collaborate with the world for the health of everyone in it. Thriving on a diverse company culture, celebrating the uniqueness of our employees and committed to inclusion. Proud to be an equal opportunity employer. Responsibilities of the position will include: Janssen Research & Development, LLC, is seeking a skilled and motivated computational chemist for the position of Scientist, Senior scientist, or Principal Scientist in our Computational Chemistry group in Toledo, Spain. We will consider candidates with a range of experience. The (Senior/Principal) Scientist will use computational methods in small molecule drug discovery projects in close partnership with chemistry and other functional Areas. A key aspect will be to apply and test new science originating from expert internal and external sources to internal projects. This will include machine learning and simulation based modeling such as moeclular dynamics and free energy caclulations. As a member of multiple drug discovery project teams, develop and execute clear computational strategies to design complex molecules and predict their properties using state-of-the-art machine learning and structure-based methodologies. Work in close collaboration with expert groups in AI/ML and simulation fields to implement novel computational approaches to aid small molecule drug Discovery. Participate in shaping and implementing structure-based strategies that support efficient drug discovery at Janssen, including advanced molecular dynamics and free energy methods. Play a leading role in collaborations with industry and academic partners and help the integration of new science to internal project applications. Ensure optimal interaction/communication with project teams, deliver impact from computational methods, and provide updates on project status to discovery leadership. Requirements qualifications: A PhD in computational chemistry or a related field with at least 2 years of experience applying computational chemistry in a drug discovery setting is preferred (either PostDoctoral or in industry). Experience in applying either machine learning or structure-based methods such as molecular dynamics or free energy methods to drug Discovery. Strong problem-solving skills for developing creative, innovative solutions, and meeting project objectives are required. Demonstrated influence, negotiation, and conflict resolution skills, including the ability to succeed within a matrix environment are required. Strong track record of scientific contributions including peer reviewed first-author publications and presentations at major meetings. Familiarity with standard computational chemistry packages (for example, Maestro/Schrodinger, MOE/Chemical Computing Group, and/or OpenEye tools or equivalent open-source tools). Ability to work closely with chemistry colleagues, a good understanding of chemistry and medicinal chemistry concepts that are applied in drug Discovery. Skills working with linux and understanding the linux working environment. Up to 10% travel both domestically and internationally is required. Interesados entrar en el enlace:
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