CHARMM-GUI
Computational Protein Design Scientist Job at CHARMM-GUI in Rockville
CHARMM-GUI, Rockville, MD, United States
CHARMM is a versatile program for atomic-level simulation of many-particle systems, particularly macromolecules of biological interest. - M. KarplusJob Title: Computational Protein Design Scientist You will:Utilize computational modeling techniques to design and predict antibody structures, including homology modeling and de novo design algorithms.Conduct in silico analysis to evaluate the binding interactions between antibodies and target antigens e.g., docking, molecular simulations.Employ bioinformatics tools and databases to analyze antibody sequence and structure data.Experience with solubility and developability algorithms for antibodies is a plus.Generate, interpret, and communicate in silico data, and communicate data with the department lead as well as with project teams.Contribute to the overall computational antibody strategy for multiple new drug R&D projects and play an active part in its implementation.Collaborate with experimental researchers to validate and optimize designed antibodies through in vitro and in vivo assays.Keep abreast of the latest developments in computational antibody design methodologies and contribute to the continuous improvement of design strategies.Present findings and progress updates to cross-functional teams and participate in project meetings.Contribute to scientific publications, external presentations, patents, and grant applications related to computational antibody design.Familiar with CHARMM, Rosetta, Gromacs, AlphaFold, ESMfold, RFdesign, ProteinMPNN, Meta dynamics, or FEP calculation.Requirements: Ph.D. in computational chemistry, bioinformatics, structural biology, medicinal chemistry, or a related field.Familiarity with antibody sequence and structure databases and bioinformatics tools.Excellent analytical and problem-solving skills.Strong communication and collaboration abilities to work effectively in interdisciplinary teams.Expertise in computational methods is highly preferred (molecular docking, homology modeling, structure- and ligand-based design, conformational analysis, molecular dynamics simulations, QSAR, binding free energy calculations).How to Apply Please send an email with your CV/resume to luke.kramer@epmscientific.com . I will be sure to respond within 48 hours to set up a time to discuss the role in further detail.#J-18808-Ljbffr