The Frederick National Laboratory is dedicated to improving human health through the discovery and innovation in the biomedical sciences, focusing on cancer, AIDS, and emerging infectious diseases.

The Biomedical Informatics and Data Science (BIDS) directorate works collaboratively and helps to fulfill the mission of Frederick National Laboratory in the areas of biomedical informatics and data science by developing and applying world leading data science and computing technologies to basic and applied biomedical research challenges, supporting critical operations, developing and delivering national data resources, and employing leading-edge software and data science.

The Strategic and Data Science Initiatives (SDSI) Program is part of the Frederick National Laboratory for Cancer Research Biomedical Informatics and Data Science Directorate. The SDSI program aims to establish new and extend current initiatives and strategic collaborations in computing and data science to address key cancer challenges, accelerate cancer research and advance predictive oncology. The SDSI program leads innovative efforts to impact and accelerate cancer research in multiple areas including increasing application of high-performance computing and AI, strategic use of data science education to build communities of practice, transforming use of large-scale data and cutting-edge data science in cancer research, and developing novel and sustainable collaborations across the NCI, academic, government, industry and international organizations.

The Accelerating Therapeutics for Opportunities in Medicine (ATOM) Consortium (atomscience.org) is a public-private partnership with the mission of transforming drug discovery by accelerating the development of more effective therapies for patients. With ATOM founding members GSK, Lawrence Livermore National Laboratory, Frederick National Laboratory, and the University of California, San Francisco, joined by Argonne National Laboratory, Brookhaven National Laboratory, and Oak Ridge National Laboratory, ATOM consortium members are developing, testing, and validating a multidisciplinary approach to drug discovery in which modern science, technology and engineering, supercomputing simulations, data science, and artificial intelligence are highly integrated into a single drug-discovery platform that can ultimately be shared with the drug development community at large. 

Frederick National Laboratory is hiring an ATOM Fellow Data Scientist to work in computationally driven cancer drug discovery as part of the ATOM Consortium.

ATOM Fellowship Program

We are currently accepting applicants for the ATOM Fellowship Program for a one-year appointment with potential of extending. Applications must include:

• A brief statement of research interests. The statement of research interests should be no more than two pages and should clearly describe how your research background and interests relate to the overall goals of the ATOM Consortium
• A brief (one paragraph) description of your career goals
• CV
• Selected applicants will be expected to give a virtual job seminar describing their current research as part of the application process. Letter of support will be requested from selected applicants' current research advisors
• More information about ATOM, the fellowship program, and frequently asked questions can be found here: https://frederick.cancer.gov/science/ATOM
  https://atomscience.org

KEY ROLES/RESPONSIBILITIES

• Be able to work independently as part of a multi-disciplinary team to support the ATOM consortium's scientific and technical goals
• Actively participate in cross-disciplinary training and collaboration
• Create and maintain strong professional relationships with all ATOM stakeholders
• Foster and nurture collaborative work environment

**THIS POSITION IS CONTINGENT UPON FUNDING APPROVAL**

BASIC QUALIFICATIONS

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

• Possession of Bachelor's degree from an accredited college/university according to the Council for Higher Education Accreditation (CHEA) in Computer Science, Math, Chemistry or Biomedical Science related field or four (4) years relevant experience in lieu of degree. Foreign degrees must be evaluated for U.S. equivalency
• In addition to the education requirement, 0-2 years of progressively responsible experience
• A strong background in any of the following: cancer biology, pharmaceutical or medicinal chemistry, pharmacology, toxicology, drug discovery, computational biology, in silico biology, bioinformatics, cheminformatics, systems biology, molecular dynamics, multi-scale modeling, machine learning, adaptive learning or high-performance computing
• Self-disciplined and willing to engage while working remotely
• Self-motivated and willing to learn and explore technology
• Ability to obtain and maintain a security clearance

PREFERRED QUALIFICATIONS

Candidates with these desired skills will be given preferential consideration:

• MS in Computer Science, Math, Chemistry or Biomedical Science related field
• Familiarity with use of machine learning and deep learning approaches including TensorFlow, Keras, and other open source packages
• Familiarity with programming tools and software typically used in data science such as Python, R, Perl, bash
  Working knowledge of bioinformatics methods and data formats (e.g., NGS, medical images, NLP, structural biology, molecular dynamic simulations, etc.)
• Familiarity in software development and engineering lifecycle
• Experience with application of machine learning/deep learning methods for medical data
• Good verbal and written communication skills
• Good interpersonal skills
• Experience working in multidisciplinary teams

EXPECTED COMPETENCIES

• Analytical approach to defining scientific questions
• Design of scientifically testable hypotheses
• Interpretation and analysis of data
• Must be detail-oriented and possess strong organizational and analytical skills with the ability to prioritize multiple tasks/projects
• Exceptional written and oral communication skills to work closely with numerous stakeholders from diverse organizations

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

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