3 Result(s)

Search for Magnetic Monopoles: from the Large Hadron Collider to Space

Student can get involved in the following aspects of the project: 1. Development of novel radiation detectors optimized for the magnetic monopole searches. The detectors are to be deployed at the Large Hadron Collider, CERN, and in space using CubeSat satellites. Experience with electronics (charge-sensitive amplifiers, impedance matching) and/or micro-fabrication techniques (physical vapor deposition, photolithography) is expected. 2. Applying Deep Learning techniques to the data analysis of the MoEDAL experiment at the LHC. The work involves operation of a GPU based computing system, application of convolutional neural networks for event classification. Prior experience with machine learning methods and/or with programming l...

Required Availability
Summer 2022
Course Credit?
Yes - PH495
Paid Position?
No

Analysis of physics data using deep learning methods

Students can work on the following projects: 1. Novel approaches to simulation of nuclear track detector data for the MoEDAL experiment at the Large Hadron Collider using Generative Adversarial Networks 2. Position reconstruction of gamma and beta decays in the EXO-200 neutrinoless double-beta decay experiment using Convolutional Neural Networks Fluency in programming languages (Python and/or C, Linux OS) are required. Familiarity with deep learning technique and relevant software (PyTorch, Keras) are preferred. Access to GPU computing system will be provided...

Required Availability
Summer 2022
Course Credit?
Yes - PH495
Paid Position?
No

Designing a low noise amplifier for detectors of elementaty particles using electronic circuit simulation techniques

Use electronics circuit simulation software to design a dedicated low noise amplifier for novel detectors of elementary particles. Requires familiarity with relevant software (e.g., LTspice)...

Required Availability
Summer 2022
Course Credit?
Yes - PH495
Paid Position?
No
Preferred Majors
Electrical Engineering
Keywords
physics | electronics
Faculty
Igor Ostrovskiy