Savannah River National Laboratory’s Environmental and Legacy Management (ELM) directorate is seeking a highly motivated and self-starting Data Scientist researcher with a focus on AI and machine learning to join their Environmental Sciences and Dosimetry team. This role involves developing cutting edge models for monitoring complex and dynamic physical systems.
Requirements
- Strong experience in Python programming, including experience with AI and machine learning libraries (e.g. Pytorch, TensorFlow, scikit-learn)
- Demonstrated ability to apply AI/ML concepts to physical systems
- Familiarity with data engineering and curation principles and practices
- Experience with data visualization tools
- Experience with machine learning primitives and ability to choose the right approach for a given problem (e.g. decision trees, random forests, deep learning)
- Experience with natural language processing (NLP) techniques and libraries (e.g. NLTK, spaCy), as well as knowledge management principles
- Python libraries: NumPy, pandas, SciKit-Learn, Pytorch, TensorFlow
Responsibilities
- Develop and maintain AI and machine learning software pipelines for monitoring complex and dynamic physical systems
- Collaborate with team members to develop and maintain research tools and software applications
- Write and maintain technical documentation for research tools and software applications
- Participate in code reviews and contribute to the improvement of the overall codebase
- Collaborate in writing proposals for external sponsors, Laboratory Directed Research and Development (LDRD) projects, and other funding opportunities
- Stay up to date with the latest developments in AI and machine learning models
Other
- The Postdoctoral Research Associate positions are fixed term assignments within the company and benefits eligible.
- Ability to obtain and maintain a security clearance, US Citizenship is Legally Required
- Excellent communication and teamwork skills
- Self-motivated and able to work independently
- Individuals must have completed all requirements for their PhD by the start of employment
