Research Internship at CKL â Optimization of Particle Detector Geometry
Research Internship at CKL â Optimization of Particle Detector Geometry
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Job Description
Position: Research Internship at CKL
Project: Optimization of Particle Detector Geometry
Scientific supervisor:Prof. Dr. Andrey Ustyuzhanin
Introduction to CKL:
The Constructor Knowledge Lab (CKL) intends to set the worldwide standard for research into Computer Science AI and Machine Learning Robotics and Neuroscience operating in strong contact with industry and:
- Leveraging CS technologies to address challenges in various fields delivering innovative solutions tailored to industry needs.
- Providing research opportunities mentorship and involvement in collaborative projects to young researchers and PhDs.
- Encouraging interdisciplinary research by fostering collaboration between diverse fields emphasizing the integration of theoretical research with practical application
Project: Optimization of Particle Detector Geometry
The goal of this project is to develop an algorithm designed to efficiently optimize the SHiP (Search for Hidden Particles) detectors straw tracker utilizing advanced sampling techniques and uncertainty estimation methods. The algorithm will aim to improve the performance of the detector by optimizing its configuration addressing challenges like high-dimensional parameter spaces noisy measurements and the need for computational efficiency in real-time data processing.
Challenges / key research questions:
- Optimize high-dimensional parameter spaces for complex detector configurations.
- Manage noisy measurements and ensure accurate results under uncertainty.
- Ensure computational efficiency for real-time data processing and decision-making.
- Balance model complexity with computational feasibility.
- Integrate uncertainty estimation techniques into the optimization process.
Requirements:
- Python skills
- Experience with AI libraries
- Prompt engineering
- Math and data processing skills are plus
Required Experience:
Intern
Employment Type
Intern
