ATOM Senior Data Scientist
Job ID: req1653
Employee Type: exempt full-time
Facility: Telework: US
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.
Our core values of accountability, compassion, collaboration, dedication, integrity, and versatility serve as a guidepost for how we do our work every day in serving the public’s interest.
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 to effectively enable and advance clinical trials.
The Strategic and Data Sciences Initiatives group in BIDS works collaboratively to continue to accelerate cancer research with a focus on increasingly effective use of data and scalable computing while guiding development of future computational infrastructure and workforce capabilities needed to address key cancer research challenges.
The Accelerating Therapeutics for Opportunities in Medicine (ATOM) consortium is a public-private partnership with the mission of transforming drug discovery by accelerating the development of more effective therapies for patients. ATOM is developing a pre-clinical drug design and optimization platform that leads with computation to help shorten the drug discovery timeline. ATOM’s approach employs data-driven modeling and computational generative molecular design to determine design criteria that consider pharmacology, safety, efficacy, and developability in the context of lead optimization. ATOM’s active learning design platform aims to selectively incorporate results from mechanistic simulation and human-relevant experimentation to generate and optimize new drug candidates significantly faster and with greater success than conventional processes. More information on ATOM can be found at www.atomscience.org.
- Responsible for leading model development efforts for ATOM in areas including cancer efficacy prediction, pharmacokinetics(PK), and pharmacodynamics (PD).
- Develop cancer efficacy and PK/PD strategies for projects from initiation through approval, including data preparation, computational predictive model development including use of machine learning, AI and simulation, subsequent data analysis and predictive model evaluation
- Provide proposals and manage the preclinical profiling (including metabolism, transporter, pharmacokinetics, pharmacodynamics, toxicology in safety, efficacy) of development compounds to support drug development
- Responsible for the analysis of bioinformatics and drug discovery data through the use of machine learning techniques, computational methods, and cloud resources to facilitate analysis of data including next generation sequencing, functional genomics data, drug data, natural language processing, molecular dynamics simulations, and image processing for use in model development
- Develop and execute modeling and simulations strategies to support Human Systems Modeling and other pilot projects
- Maintain up-to-date knowledge of drug discovery regulatory requirements
- Engage and work with peers and management teams for input into development and pilot projects to complement in-house knowledge and expertise
- Engage and work with business development team and potential partners for technological assessments as well as collaborate with outside organizations on emerging technical capabilities
- Support development and testing of data science workflows implemented on High Performance Computing and Cloud systems
- Drafts, writes and edits literature review, scientific reports, papers, journal articles and abstracts and present achievements to support ATOM’s integrated research and evidence-based practice
- Future responsibilities may include supervision of fellows, interns, and other team members
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 areas related to life science, computer science, data science, or biomedical informatics 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, a minimum of eight (8) years of progressively responsible experience
- Minimum eight (8) years of experience working in drug development in a pharma or research in support of clinical development of compounds
- 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.)
- Self-disciplined and willing to engage while working remotely
- Self-motivated and willing to learn and explore technology
- Ability to obtain and maintain a clearance.
Candidates with these desired skills will be given preferential consideration:
- Possession of a PhD from an accredited college or university according to the Council for Higher Education Accreditation in areas related to life science, computer science, data science or biomedical informatics
- Training and experience in cancer efficacy model development and/or pharmacokinetics and pharmacodynamics and application in drug development is preferred
- 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
- Experience in fast paced, matrix environment desirable
- Ability to work independently
- Experience managing vendors
- Ability to work with ease in a fast paced, agile environment
- Self-motivated and result-oriented, able to handle multiple projects efficiently
- Excellent communication and interpersonal skills
- Must be a team player
Equal Opportunity Employer (EOE) | Minority/Female/Disabled/Veteran (M/F/D/V) | Drug Free Workplace (DFW)