Scientific Calendar Event

Starts 25 Mar 2024 16:00
Ends 31 Mar 2024 00:00
Sherubtse College, Royal University of Bhutan, Kanglung, Trashigang
Physics Without Frontiers working with the University of Sussex, and DISCnet are organising a 5-day intensive workshop in Symmetries, Data Science, and AI for Physicists for over 90 physics students. The workshop will consist of lectures in the morning, followed by hands-on sessions in the afternoons where participants will be analysing Open Data from the ATLAS experiment at CERN and have problem solving sessions. The participants will learn about particle physics and symmetries, they will gain analytical skills, and be given an introduction to Machine Learning (ML), and use ML to search for Dark Matter in ATLAS proton collision data. There will be a careers and opportunities session, and the participants will give presentations at the end and receive certificates. The workshop is taught by Dr Kate Shaw (ICTP, University of Sussex), Dr Mick Taylor (Universityof Sussex), and Sr Andrea Banfi (University of Sussex), and coordinated by Mon Badadur Ghalley (Sherubtse College, The Royal University of Bhutan). By actively engaging in the workshop, students will gain the skills to effectively employ advanced data science and computational tools in the field of physics. They will also develop an understanding of the significance of symmetries in physics, thereby strengthening their ability to conduct scientific analysis, modelling, and problem-solving on a global level. Goals and deliverables • Teach students from Sherubtse College through hands-on session and lectures on symmetries, data science and AI. • Support students to enhance proficiency in computational physics during the workshop and provide the tools so that they may continue their learning. • At the conclusion of the workshop, students will deliver presentations summarising their learning experiences. • Top students will be mentored to pursue studies abroad, giving advice and recommendations about scholarships at international programs.