4 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 the Low Earth Orbit using CubeSat satellites. No prior experience with detector development required. 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. No prior experience with machine learning methods required. Familiarity with programming languages (Python, C) is advantageous. Position is initially unpaid. ...

Required Availability
Fall 2017 | Spring 2018 | Summer 2018
Course Credit?
Yes - PH495
Paid Position?
No

Biomedical sensors

We have several projects that deal with development and testing of biomedical instrumentation. Depending on the project, the students may participate in several related research activities: 1) Sensor design, manufacture and testing. Practical hands-on tasks that often need 3D design skills, working with plastics, resins and other materials. 2) Signal processing and pattern recognition of signals collected by our sensors. The sensors are used in the human studies and the collected data need to be processed to recognize events of interest in the sensor data. Either direction can be used as a credit in research scholars program or for conference paper preparation....

Required Availability
The End of Time
Course Credit?
Yes - Research Scholars
Paid Position?
No

Optimization in big data: algorithms and applications

This is a research position with Dr Yangyang Xu in optimization and its applications. The data in modern applications is becoming extremely big. The data size grows significantly faster than the computer development speed. That means running classic methods on modern computers cannot handle modern problems with huge-scale data. Therefore, more advanced algorithms are required. The students will be advised to read recent papers, implement existing and/or new optimization algorithms, and also do applications in statistical and machine learning, image processing, and finance. If you are interested, please contact with Yangyang Xu at yangyang.xu@ua.edu. A CV and transcript are required....

Required Availability
Fall 2016 | Spring 2017
Course Credit?
No
Paid Position?
No

Data analysis and optical simulation for the EXO-200/nEXO experiments

Students can work on the following aspects: 1. Development of data quality scripts for the EXO-200 experiment. 2. Understanding light propagation in the EXO-200/nEXO detectors using novel GPU-based optical simulation software. 3. Using convolutional neural networks and other Deep Learning techniques for the EXO-200 data analysis and reconstruction. The work with be performed using the in-house GPU based computing system and the NERSC supercomputer facility at Berkeley. No prior experience with machine learning methods is required. Familiarity with programming languages (Python and/or C) is advantageous. Position is initially unpaid....

Required Availability
Spring 2018 | Summer 2018 | Fall 2017
Course Credit?
Yes - PH495
Paid Position?
No