Speaker
Description
LIV.INNO is a new initiative which will train around 40 PhD students over three cohorts. It fosters innovation in data-intensive science, serves as a dynamic platform for collaboration between leading research organizations and the next generation of scientists. Within this context, several projects focus on research that intersects between data science and particle accelerator research.
This contribution showcases the early results from studies into optical transition radiation diagnostics for low energy ion beams, tailored Monte Carlo simulations for reactor ap-plications, and the reconstruction of the transverse beam distribution using machine learning. These early insights highlight the many benefits from collaborative R&D in data-rich accelerator environments. A summary of the training events offered by the center is also given.
Funding Agency
This work was supported by the Science and Technology Facilities Council (STFC) under grant agreement ST/W006766/1.
| Region represented | Europe |
|---|---|
| Paper preparation format | Word |
