Team Lead/Senior Scientist - Computational Chemistry (NCI)

21701, Frederick
Sep 24, 2018
Required Education
Position Type
Full time


The Cancer Research Technology Program (CRTP) develops and implements emerging technology, cancer biology expertise and research capabilities to accomplish NCI research objectives. The CRTP is an outward-facing, multi-disciplinary hub purposed to enable the external cancer research community. A major focus of the CRTP is the NCI RAS Initiative with the goal to discover new therapeutic interventions against RAS-driven cancers.


The Cancer Research Technology Program (CRTP) within the Frederick National Laboratory for Cancer Research (FNLCR) serves as the hub for the NCI RAS Initiative. One of the major objectives of the RAS initiative is to carry out structure-based drug discovery to identify lead compounds against RAS-driven cancers. The candidate will join the RAS Initiative and initiate/lead the projects on developing and optimizing small molecules for use as RAS inhibitors. The key roles and responsibilities for this position will be to:

  • Work closely with a highly collaborative multidisciplinary team of chemists, biochemists, biophysicists, and cell and structural biologists at the NCI RAS Initiative to develop and optimize small-molecules for use as RAS inhibitors
  • Perform structure-based computer aided drug-design using the structures of oncogenic RAS mutants, and RAS-complexes with various effectors and regulatory proteins
  • Provide computational support during hit validation studies
  • Conduct hit-to-lead computational chemistry efforts around various targets/screens that yield advanceable hits
  • Participate in project-based team meetings to identify and solve problems, and plan future strategies


Basic Qualifications:

To be considered for this position, you must minimally meet the knowledge, skills, and abilities listed below:

  • Possession of a PhD in a field related to computational chemistry or in a related discipline from an accredited college or university according to the Council for Higher Education Accreditation (CHEA) appropriate to biomedical research (Additional qualifying experience may be substituted for the required education); Foreign degrees must be evaluated for U.S. equivalency.
  • In addition to educational requirements, a minimum of five (5) years post-graduate experience of competent, innovative research in a field of specialty
  • Proven expertise in structure based drug design (SBDD), virtual screening, molecular dockings, molecular dynamics simulations, free energy calculations, quantitative structure-activity relationship (QSAR), pharmacophore based, two-dimensional and three-dimensional structure based screening, including substructure, similarity, and diversity search, core hopping, computer-aided drug discovery, cheminformatics, chemical information database designing, mining and analyzing
  • Expertise in modelling, docking and MD softwares: Modeller, Autodock, Schrodinger package, Amber, Gromacs, APBS, Gaussian, MMTSB, NAMD, ZDOCK
  • Knowledge of computer languages and OS scripting: C, C++, Perl, Bioperl, Python, Unix shell scripting, R-language
  • Track record of accomplishments in drug discovery and/or molecular modelling
  • Knowledge of biochemical and biophysical techniques (SPR, ITC, LC-MS etc.) to characterize protein-small molecule binding interactions
  • Familiar with chemical shift perturbation experiments using 2D 1H–15N HSQC to confirm binding of small molecules
  • Must be able to obtain and maintain a security clearance
  • Preferred Qualifications:

    Candidates with these desired skills will be given preferential consideration:

  • Experience of working with RAS/small GTPases
  • 5+ years of experience in small molecule drug discovery in biotechnology or pharmaceutical setting
  • Expected Competencies
  • Must be highly collaborative, self-motivated and able to work effectively as part of a multidisciplinary team
  • Highly organized with excellent analytical, documentation and multi-tasking skills
  • Ability to efficiently manage workload over multiple projects