Postdoc Research Associate - Data Scientist
Aiken, SC, United States
⚠️ We'll shut down after Aug 1st - try foo🦍 for all jobs in tech ⚠️
Full Time Mid-level / Intermediate Clearance required USD 96K - 179K * est.
Savannah River National Laboratory
We put science to work. We protect our environment, secure our clean energy future, serve our national defense and reduce emerging nuclear threats.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. The successful candidate should have strong software development experience in Python and broad knowledge of AI and machine learning techniques and an ability to apply them to broad problem sets in areas such as bioengineering, environmental monitoring, and national security related domains.
The Postdoctoral Research Associate positions are fixed term assignments within the company and benefits eligible.
- 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
Typical Tools and Technologies:
- Python libraries: NumPy, pandas, SciKit-Learn, Pytorch, TensorFlow
- Data visualization tools: Plotly/Dash, Matplotlib, Seaborn
- Machine learning frameworks: SciKit-Learn, Pytorch, TensorFlow
- Others as the technology stack changes
Minimum Qualifications:
- PhD + 0-3 yrs in computer or physical sciences
- Ability to obtain and maintain a security clearance, US Citizenship is Legally Required
- 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
- Excellent communication and teamwork skills
- Ability to write and document technical work
- Self-motivated and able to work independently
- Familiarity with data engineering and curation principles and practices
- Experience with data visualization tools
- Individuals must have completed all requirements for their PhD by the start of employment
- Must have the ability to obtain and maintain an appropriate level U.S. Government security clearance for which U.S. Citizenship is legally required.
Preferred Qualifications:
- Experience in software development, preferably in a research environment
- 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
- Experience with proposal writing and research funding opportunities
"We put science to work!"
Savannah River National Laboratory (SRNL) is a multi-program laboratory applying state of the art science and practical, high-value, cost-effective solutions to complex technical problems to protect the nation. Located at the U.S. Department of Energy’s (DOE) Savannah River Site (SRS) in Aiken SC, the laboratory develops and deploys innovative technologies to address some of the nation’s environmental, energy, and national security challenges.
Battelle Savannah River Alliance (BSRA) is constantly assessing trends to provide the best possible benefits to our workforce. We also negotiate cost effective premiums that will meet the needs of our evolving workforce.
Some of the *Benefits offered to employees include:
*Benefits vary based upon employment status
- Highly competitive Medical, Dental, and Vision options including HSA options with company provided seed
- Short- & Long-Term Disability (company paid)
- Life Insurance Non-Contributary 1X salary (company paid)
- AD&D Non-contributary 1x salary (company paid)
- Savings & Investment plan:
- Qualified Non-Elective Company Contribution of 5% each pay period with immediate vesting
- Company match 50 cents/dollar up to 8% (3 yrs. vesting in company match)
- Contributory Life Insurance up to 5x Salary with $1M Cap
- Contributory AD&D (employee, spouse and children)
- Paid Time Off
- Employee Assistance Plan
- SRNL offers a competitive relocation package to ease the transition process. Domestic and international relocation assistance is available for certain positions.
For more information about our benefits, working here, and living here, visit the “About” tab at www.srnl.doe.gov.
BSRA is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, or protected veteran status. BSRA is also committed to making our workplace accessible to individuals with disabilities and will provide reasonable accommodations, upon request, for individuals to participate in the application and hiring process. Please email us at SRNLRecruiting@srnl.doe.gov with any questions regarding the hiring process or to request an accommodation.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Data visualization Deep Learning Engineering Machine Learning Matplotlib ML models NLP NLTK NumPy Pandas PhD Pipelines Plotly Postdoc Python PyTorch Research Scikit-learn Seaborn Security spaCy TensorFlow
Perks/benefits: Career development Competitive pay Health care Insurance Relocation support Startup environment
More jobs like this
Explore more career opportunities
Find even more open roles below ordered by popularity of job title or skills/products/technologies used.