ATOM Fellow - Data Scientist I

Job ID: req3047
Employee Type: exempt full-time
Division: Cancer Research Technology Program
Facility: Telework: US
Location: 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

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, multidisciplinary hub purposed to enable the broader cancer research community. As part of the CRTP, the Cancer Data Science Initiatives (CDSI) group establishes and extends computational and data science initiatives and strategic collaborations to address key cancer challenges, accelerate cancer research, and advance predictive oncology. CDSI has a leadership role in several collaborations, including the partnership between the National Cancer Institute and the Department of Energy (DOE) to simultaneously accelerate advances in precision oncology and scientific computing. These collaborations are growing and have developed innovative artificial intelligence (AI) resources, technologies, and collaborative research opportunities that are shaping the future of predictive oncology, drug discovery, and clinical applications for cancer.

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, current 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 Data Science Fellow to work in computationally-driven cancer drug discovery as part of the ATOM Consortium.

KEY ROLES/RESPONSIBILITIES

• Will work independently and 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

BASIC QUALIFICATIONS

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

• Possession of a Bachelor's degree in Biomedical Sciences, Computer Science, Math, Chemistry and/or Biomedical Science related field from an accredited college or university according to the Council for Higher Education Accreditation. Foreign degrees must be evaluated for U.S. equivalency.
• A strong background in any of the following: computer programming, synthesis chemistry, pharmacology, toxicology, drug discovery, computational biology, cheminformatics, cancer biology, systems biology, molecular dynamics, multiscale modeling, machine learning, convolutional neural network, and familiarity with working in cloud environment.
• Familiarity with programming tools and software typically used in data science such as Python, R, Perl, bash
• Good coaching skills. Experience mentoring or teaching students and ability to develop interesting contents/projects for students.
• Experienced with scientific presentations in public.
• Ability to obtain and maintain a security clearance

PREFERRED QUALIFICATIONS

Candidates with these desired skills will be given preferential consideration:

• Ph.D. in Biomedical Sciences, Data Science, Computer Science, Math, Chemistry or Biomedical Science related field
• Familiarity with use of machine learning and deep learning approaches including Convolutional Neural Network, TensorFlow, Keras, and other open source packages
• Experience with applications of machine learning /deep learning methods for biomedical or chemical data sets
• Working knowledge of cheminformatics methods and data formats (e.g., SMILES/sdf, biomedical images, NLP, structural biology, molecular dynamic simulations, etc.)
• Familiarity with chemical synthesis, synthetic biology and/or AI-driven generative molecular design
• Familiarity in software development and engineering lifecycle
• Good verbal and written communication skills.
• Good interpersonal skills.
• Success working in multidisciplinary teams.
  
• Self-disciplined but willing to learn and explore technology
  
• Self-motivated and able to work remotely

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

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