Computational Scientist I

Job ID: req2599
Employee Type: exempt full-time
Division: Cancer Research Technology Program
Facility: Frederick: ATRF
Location: 8560 Progress Dr, Frederick, MD 21701 USA

The Frederick National Laboratory is a Federally Funded Research and Development Center (FFRDC) sponsored by the National Cancer Institute (NCI) and operated by Leidos Biomedical Research, Inc. The lab addresses some of the most urgent and intractable problems in the biomedical sciences in cancer and AIDS, drug development and first-in-human clinical trials, applications of nanotechnology in medicine, and rapid response to emerging threats of infectious diseases.

Accountability, Compassion, Collaboration, Dedication, Integrity and Versatility; it's the FNL way.

PROGRAM DESCRIPTION

We are looking for a motivated Scientist to join the RAS Computational Chemistry (RCC) Team which is part of the NCI RAS Initiative. Our focus in the RCC Team is applying (and developing) computational methods to aid drug discovery efforts at the RAS Initiative. We are targeting the RAS proteins-which are implicated in over 20% of human cancers and are important drug targets-as well as RAS related proteins and RAS effectors. Our main tool is UCSF DOCK, which we use for performing large scale screens of hundreds of millions of molecules. We also use chemical informatics methods and Molecular dynamics combined with free energy calculations mainly to support our docking calculations. We are highly collaborative and support other mostly wet lab teams within the RAS Initiative. The NCI RAS initiative is a part of the Cancer Research Technology Program (CRTP) at the Frederick National Laboratory for Cancer Research (FNLCR). 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.

e.KEY ROLES/RESPONSIBILITIES

The key roles and responsibilities for this position are to:

• Work as part of the RAS Computational Chemistry (RCC) team
• Perform computational ligand (drug) discovery (by screening large virtual databases of hundreds of millions of small molecules using docking software) against RAS using the structures of oncogenic RAS mutants, and RAS-complexes with various effectors and regulatory proteins
• Optimize hits using computational methods including chemical informatics methods and free-energy calculations
• Test (and aid in developing) new docking methods for improving our computational screening against RAS
• Present research findings within the group and at national meetings and publish findings in peer reviewed journals
• 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

BASIC QUALIFICATIONS

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

• Possession of a Ph.D. in computational chemistry or computational biology (or related field) from an accredited college or university according to the Council for Higher Education Accreditation (CHEA). (Additional qualifying experience may be substituted for the required education). Foreign degrees must be evaluated for U.S. equivalency
• Knowledge of computational techniques for drug discovery: molecular docking, and/or molecular dynamics
• Ability to obtain and maintain a security clearance

PREFERRED QUALIFICATIONS

Candidates with these desired skills will be given preferential consideration:

• Expertise in structure-based drug design (SBDD), e.g. virtual screening, molecular docking, molecular dynamics simulations, free-energy calculations, computer-aided drug discovery, and/or cheminformatics
• Expertise in molecular docking software (e.g. UCSF DOCK, Autodock, or Glide (Schrodinger))
• Experience with molecular modeling and molecular dynamics software (e.g. AMBER, NAMD, or GROMACS)
• Knowledge of scripting and computer languages, e.g. Python, Unix shell, R, C++, or Fortran
• Experience working with RAS/small GTPases
• Knowledge of biochemical and biophysical techniques (SPR, ITC, LC-MS, etc.) to characterize protein-small molecule binding interactions
• Good written and oral communications skills
• Must be collaborative, self-motivated, and able to work effectively as part of a multidisciplinary team

Equal Opportunity Employer (EOE) | Minority/Female/Disabled/Veteran (M/F/D/V) | Drug Free Workplace (DFW)

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