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Algorithm Development, InformaticsPosted by: National Institutes of Health (NIH)
Posted date: 2020-Feb-21
NCATS is one of the 27 Institutes and Centers at the National Institutes of Health (NIH). The Informatics group collaborates closely with biologists and chemists to develop robust assay designs, analyze experimental outcomes and validate new hypothesis. NCATS' informatics personnel perform a variety of ligand- and protein structure-related modeling tasks, support the drug discovery process and accelerate translational sciences. The team members also are developing infrastructure and software for the meta-analysis of high-content screens and for integration of the existing biomedical data to discover new hypothesis.
NCATS' Informatics group is seeking a creative, self-motivated postdoctoral informatics scientist to develop new algorithms for prediction of i) protein-ligand interactions; ii) chemical reactions and comprehensive support of drug discovery projects. The postdoctoral fellow will be responsible for uploading and analyzing pilot and quantitative high-throughput screening runs; analyzing assay reproducibility; analyzing confirmation and secondary screening assays; developing and applying QSAR models and molecular modeling for virtual screening of compounds; supporting medicinal chemistry efforts; and developing new algorithms for prediction of protein-ligand interactions and chemical reactions. Research will be conducted in the NCATS Informatics group.Qualifications:
The ideal candidate will possess a minimum of a Ph.D. in computational science/bioinformatics with specialization in machine learning. He or she will have published at least three research articles as first author. The incumbent must have experience with common cheminformatics libraries and data formats (e.g., RDKit, OpenBabel, SMILES, InChi, etc.), modern software packages (e.g., MOE/CCG, OpenEye tools) and scientific programming (e.g., Python, JAVA) and data analytics (e.g., KNIME, Spotfire). He or she must be able to script workflows and implement new algorithms, have experience working with multi-disciplinary teams, and possess strong oral and written English communication skills. He or she should have experience using modern machine learning and deep learning frameworks (e.g., TensorFlow, Keras), as well as experience in developing algorithms for prediction of protein-ligand interactions and/or chemical reactions.To Apply:
Applicants should submit a cover letter describing your interest in this position, a current curriculum vitae, and complete bibliography to Dr. Alexey Zakharov at alexey.zakharovnih.gov. The review of applications will begin immediately and will continue until the position is filled.
The NIH is dedicated to building a diverse community in its training and employment programs. NIH is an Equal Opportunity Employer.