What your job will be like:Work on all elements of the data science workflow (data preprocessing, analyzing data using exploratory mathematics, statistical techniques, developing and optimizing AI/ML models, developing agentic workflows). Recommend various technology options or approaches for system and processes improvements in terms of performance, efficiency, cost or safety.
In this job you will:- Participate in the research and development in machine learning and data science focused on applications such as:
- AI/ML based active control of large complex systems
- Surrogate modeling of particle accelerator processes, deployment and continual learning workflows
- Uncertainty Quantification for ML
- Conduct technical research in areas of interest to the projects.
- Publish research results in highly visible, peer-reviewed venues (conferences, workshops & journals).
- Develop and maintain high quality software for data science projects (machine learning, continual learning, uncertainty quantification).
- Interact with internal and external researchers and domain scientists for collaboration purposes.
- Participate and potentially lead technical presentations on the work.
- Participate in team meetings and develop ideas for new projects/proposals.
Additional ResponsibilitiesLead - Supervisory - ManagementExperience- Required: none
- Preferred: 2 or more years of postdoc experience
- Preferred: experience with contributing and leading tasks on large projects with multi-disciplinary teams.
Education- Required: Bachelor's Degree Computer Science, Data Science, Applied Mathematics, Computer Engineering, or a closely related technical area
- Preferred: Ph.D.
Experience and Education ExchangeEducation above the minimum may be substituted for experience. Relevant experience may not be substituted for education.
Licenses and CertificationsKnowledge, Skills, and Abilities- Proficiency in Python and familiarity with publicly available technical libraries for data analytics (e.g. scikit-learn), deep learning (e.g. Pytorch, Tensorflow) and optimization tools
- Proficiency in advance machine learning such as uncertainty quantification for ML, continual learning, graph neural networks
- And/or proficiency in agentic workflow tools such as LangChain, LangGraph
- Ability to operate computer equipment in an office or laboratory environment
- Strong interpersonal skills and ability to effectively work on project teams
- And/or proficiency in Large Language Models training and evaluation
- Ability to work with large datasets and mine relevant information for use in AI/ML applications
- Proactive, highly motivated self-starter
- Ability to develop approaches and solutions to complex problems in the forms of proposals, software, documents or other work products
- Ability to clearly communicate and report the progress on tasks and projects
Additional Licenses and Certifications 
