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Machine Learning / Computational Chemistry

National Center for Advancing Translational Sciences, Bethesda, MD and surrounding area

Position Description:

NCATS, a major research component of NIH, seeks applications from qualified candidates to fill antiviral discovery informatics postdoctoral fellow positions in the Antiviral Program for Pandemics (APP) within the Center’s Division of Preclinical Innovation. Multiple positions are available for motivated individuals to work in a translational science laboratory team environment with a focus on multiple target-based programs, including assay development, high-throughput screening and drug lead optimization.
 
Launched in June 2021 with more than $3 billion in funding from the American Rescue Plan, the APP will accelerate the development of a portfolio of promising antivirals that can move rapidly into later-stage clinical trials to combat future pandemics. Having safe and effective oral antiviral candidates ready for deployment in later-stage clinical trials against a newly emergent virus would save lives, reduce serious illness and prevent overwhelming surges in hospitalizations during a viral outbreak or pandemic. NCATS will partner with extramural scientists and the private sector to advance drug discovery and development programs for oral antiviral candidates. NCATS can collaborate on projects with entry points anywhere along the development pipeline — and with flexible project exit points — to accelerate discovery and overcome the scientific, technical and enterprise barriers to delivering drug candidates ready for Phase 2 clinical trials in future pandemics.
 
Core Responsibilities:
The selected candidates will work as part of a multidisciplinary team of innovative scientists using cutting-edge technologies for the development of antiviral drugs. The postdoctoral fellows will be responsible for developing new algorithms for the prediction of protein–ligand interactions and deep generative models, developing and applying QSAR models and molecular modeling techniques for the virtual screening of compounds, and lead optimization efforts. Candidates should be self-motivated, driven, thorough and careful experimentalists with the ability to multitask, think independently and work in a highly creative, interactive and fast-paced environment. In addition to teamwork, they also will be expected to work independently as well-trained problem solvers. Effective communication and presentation skills are required. The selected candidate will keep accurate and complete records of all scientific experiments according to established procedures and ensure that these records and raw data are properly retained. They will draft technical reports, manuscripts and patent applications and present work to internal and external collaborators as needed.
 

Qualifications:

Applicants to this postdoctoral fellow position must possess a Ph.D. in computational science or bioinformatics with a specialization in machine learning or computational chemistry. Candidates with previous experience with common cheminformatics libraries and data formats (e.g., RDKit, OpenBabel, SMILES, InChi), modern software packages (e.g., MOE/CCG, OpenEye tools), scientific programming (e.g., Python, JAVA) and data analytics (e.g., KNIME, Spotfire) are preferred.
 
Stipends/Benefits:
The salary will be commensurate with experience, based on the NIH Postdoctoral Intramural Research Training Award and Visiting Fellow scale; medical insurance coverage will be provided. The position is renewable for up to five years.
 

To Apply:

Interested candidates should email a cover letter describing their research and career goals, a current curriculum vitae with a complete bibliography, and the names of and contact information for three references to NCATS APP Hiring at NCATSAPPHiring@nih.gov. Applicants also should indicate when they are available to start. Please note that the starting date of the fellowship is flexible, preferably within 2021.
 
The review of applications will begin immediately and will continue until the position is filled. Learn more about NCATS’ role in the APP.
 
 

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