CHARMM-GUI
Computational Protein Design Scientist
CHARMM-GUI - Rockville
Work at CHARMM-GUI
Overview
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Overview
CHARMM is a versatile program for atomic-level simulation of many-particle systems, particularly macromolecules of biological interest. - M. Karplus
Job 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 . I will be sure to respond within 48 hours to set up a time to discuss the role in further detail.
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