AI Computational Scientist

Brookhaven National Laboratory•Ridge, NY

1d•$154,250 - $235,000•Onsite

About The Position

The NSLS-II beamlines provide world-class facilities for research. The increased brilliance of the source, along with automation for data analysis has led to a significant increase in the acquisition speed and the amount of data which must be processed and analyzed by NSLS-II users. It is therefore essential to provide advanced tools making use of artificial intelligence and machine learning for data acquisition and data analysis and to work with the diverse user community of the NSLS-II in developing these tools. NSLS-II has initiated AI pilot programs to further the development of these techniques. We are looking to recruit a scientist to work on Ai and machine learning developments for synchrotron applications, notably for applications where data analysis and management coupled with automated data collection would provide a large benefit to the experimental process. The work will take place the Data Science and Systems Integration (DSSI) in close collaboration with beamlines beamline groups.

Requirements

PhD degree in Physics, Biology, Computer Science, Science or similar area
At least 10 years of experience in synchrotron light source science.
Curiosity, good communication skills and ability to work in large multi-disciplinary teams.

Nice To Haves

Demonstration of the deployment machine (deep) learning developments ideally for synchrotron data analysis or similar
Strong programming skills in Python GPU programming (CUDA, OpenCL) is a plus.
Experience in working with collaborative open-source projects for science and/or engineering.

Responsibilities

Development of innovative machine-learning based algorithms for data acquisition and online data processing.
Organize data, meta-data standards, provide mechanisms for distributing data and analysis tools for integration of NSLS-II results in a broader context.
Conduct original research project exploiting machine learning for synchrotron applications with NSLS-II science programs.
Work with scientists and engineers at NSLS-II, user groups and research sponsors to disseminate knowledge about the use of artificial intelligence and machine learning for light source science applications.