Master in particle physics
The particle physics department (DPNC) studies the fundamental structures and laws of nature from the largest dimensions in the Universe to the smallest of the microcosm by using three complementary approaches:
- High-energy particle collisions with CERN’s LHC and the ATLAS detector, and ideas for future accelerators such as the FCC hh-ee-he
- Experiments with neutrinos (T2K, Hyper-Kamiokande) , astroparticle physics experiments on the ground (IceCube, CTA) and in space (AMS, POLAR-2, DAMPE, PAN, HERD)
The groups involved in these fundamental physics and astrophysics researches are also involved in projects in medical physics and other social aspects (diversity & gender, climate monitoring, big data and AI, outreach, new materials...).
DURATION OF STUDIES
2 years (4 semesters)
60 ECTS for courses + 60 ECTS for thesis
LANGUAGE OF INSTRUCTION
Deadline: 30 April
(28 February for applicants subject to a visa because of their nationality, as set forth in Swiss federal regulations)
The research conducted at DPNC finds its motivation in the grand mysteries of the Universe
which can be formulated in form of open questions:
- What is the nature of Dark Matter and Dark Energy?
- Can gravity be incorporated in the particle picture?
- Why are the neutrino masses so small and what can neutrinos teach us about the matter / anti-matter asymmetry?
- What are the laws of physics at extremely high energy?
- What can we learn about our Universe from cosmic rays?
- What is the physics behind the most extreme processes in the Universe?
- Is the hierarchy problem, i.e. the Higgs mass being so much smaller than the Planck mass, a broad hint or a deception?
- Is there physics Beyond the Standard Model of Particle Physics?
- How can novel solutions on particle physics detectors produce a benefit in medical physics?
The proximity to and close connection with CERN and its Large Hadron Collider plays a key role in the department’s research program. The Department is also involved in Astroparticle Physics activities through APPEC.
Artificial intelligence and in particular machine learning has great prospects to help us unlock the mysteries of the Universe. Promising areas of the application of machine learning and in particular Deep Neural Networks to the LHC physics program and in the Cherenkov Telescope Array (CTA) experiment include big data handling and filtering, anomaly detection in data, fast track reconstruction and fast detector simulation as well as particle and event classification.
On top of that we also have additional optional courses offered to our students either from our department or from other departments and from other master programs:
All members of our group will be happy to help master’s students in their search for a degree topic, and supervise them during the master’s project:
Giuseppe Iacobucci : ATLAS et FASER (LHC)
Philippe Mermod : ATLAS et MoEDAL (LHC)
Tobias Golling : ATLAS (LHC)
Anna Sfyrla : ATLAS et FASER (LHC)
Xin Wu : ATLAS (LHC)
Teresa Montaruli : CTA and ICECUBE
Xin Wu : AMS, DAMPE, POLAR-2, PAN, HERD
Federico Sanchez Nieto : T2K and HyperK
Renaud Jolivet : Neuroscience
Giuseppe Iacobucci : TT-PET
Magda Kowalska : Nuclear physics & biology
Connect with us at: https://twitter.com/DPNC_Unige