Jefferson Lab is looking to solve problems in data science and machine learning to support its mission projects
Requirements
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
Ability to work with large datasets and mine relevant information for use in AI/ML applications
Ph.D. in Computer Science, Data Science, Applied Mathematics, Computer Engineering, or a closely related technical area (preferred)
2 or more years of relevant postdoctoral experience (preferred)
Familiarity with deep learning frameworks such as Pytorch, Tensorflow
Familiarity with optimization tools
Ability to develop approaches and solutions to complex problems in the forms of proposals, software, documents or other work products
Responsibilities
Participate in the research and development of machine learning and data analysis focused on applications such as: Generative machine learning methods, Reinforcement learning and deep model predictive control, Uncertainty quantification for machine learning
Conduct technical research in areas of interest to the projects
Publish research results in highly visible, peer-reviewed venues (conferences & journals)
Develop and maintain high quality software for data science projects
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 interact with funding clients
Other
Bachelor's Degree in Computer Science, Data Science, Applied Mathematics, Computer Engineering, or a closely related technical area
2 or more years of relevant postdoctoral experience (preferred)
Ability to clearly communicate and report the progress on tasks and projects
Strong interpersonal skills and ability to effectively work on project teams
Must be able to operate computer equipment in an office or laboratory environment
