Principal Scientist - CADD

The Computer-Aided Drug Discovery (CADD) group in Emeryville, CA is seeking a new team member to complement our skills and enthusiasm for impacting human health through drug discovery. Our Emeryville site uniquely houses the Novartis Institutes for Tropical Diseases that contributes to a pipeline of medicines for major global health challenges including malaria, Chagas disease and pandemic preparedness. <br><br>As part of the Emeryville Protein Interactomics Center, we contribute to drug discovery and technology developments across all research sites, disease areas, and technology platforms. In all our endeavors, we build on NIBR’s vast knowledgebase of over 20 million activity measurements, internal proprietary structural database, a global CADD team and the partnership and expertise of over 5,000 scientists with a huge variety of expert skills and a strong dedication to innovation.<br><br>At the Novartis Institutes for BioMedical Research (NIBR), we value your ideas, personal growth and career aspirations. You will have opportunities to explore the power of cutting-edge science and technology (e.g., cryoEM, VR, high performance compute environment) in an environment that truly values multidisciplinary collaborations. We are a highly-regarded research group that values engagement in the wider scientific community. In order to tackle the world’s toughest medical challenges, you will be empowered to take smart risks in an unbossed way, using your creativity and resourcefulness.<br><br>This exciting role is based out of our Bay Area location (Emeryville), with a hybrid work model (office/home).<br><br>Your responsibilities include, but are not limited to:<br><br>Leverage your CADD expertise to engage and influence multidisciplinary project teams for effective decision-making from target identification through candidate nomination <br><br>Generate 3D structural understanding of the mechanism of action for novel ligands using advanced molecular modeling, solvation considerations and molecular dynamics simulations in close collaboration with experimental scientists<br><br>Drive compound optimization cycles by participation in rational drug design and synthesis prioritization efforts via advanced scoring methods (active learning and ML model development, free-energy perturbation or alternate scoring method), in multi-objective fashion<br><br>Develop, improve and implement efficient computational workflows that can be distributed to our global CADD team<br><br>Initiate drug discovery efforts by proposing novel targets / modalities, evaluating target druggability and executing in silico hit generation, triage and expansion methodologies<br><br>Keep abreast of scientific developments and interact with internal and external scientists to integrate novel insights into computational approaches for drug discovery<br><br><br>[#video#https://www.youtube.com/watch?v=ggbnzRY9z8w{#400,300#}#/video#]