The project will be covering your residence fees during the year in the U.K as well as subsistence (Food, travel, books, extra ~£530 pm), for a total or ~£17.6k for the 12 months stay and travel costs (~£1.3k). The project does not fund Masters in research fees.
Following are the research projects available:
University of Strathclyde :
- Manufacture and characterisation of large area mirror coatings for use in gravitational wave observatories
- Use of high energy ion beam deposition for manufacturing advanced mirror coating materials for gravitational wave observatories.
Background: The Department of Biomedical Engineering at the University of Strathclyde hosts a broad range of manufacturing facilities for the deposition of advanced optical coatings, including the world’s largest ion beam deposition system in terms of uniformity area located at Extreme Performance Optical Coating. The proposed MRes projects will explore the use of standard and high energy deposition technologies and study the optical and mechanical changes due to post-deposition heat treatment. Within the labs there will be access to characterisation methods including photothermal absorption, cavity ringdown, spectrophotometry, mechanical loss (GeNS), and microscopy (optical, SEM).
Supervisory team: Dr Mariana Fazio and Prof Stuart Reid, and the projects will be carried out with the Optics Working Group (OWG) of LIGO and will rely on strong links with other LSC groups especially those located at Glasgow and Caltech.
The fees for September/October 2024 intake are £28,250. Please check funded scholarships and faculty of Engineering International Scholarships Postgraduate 2024/25 for scholarship options.
*Please apply by going to the PGR applications page and choose at the bottom MRes and Biomedical Engineering (2024) which should take you to this page to confirm your email address for the application.
University of Glassgow:
1. A Machine Learning Approach to Suspension Control in Gravitational Wave Detectors:
The control systems of gravitational wave detectors such as Advanced LIGO are incredibly complex systems consisting of hundreds of input and output data channels to a complexly coupled system and represents a highly challenging optimisation problem because the system includes many unknown couplings, non-linear effects, and non-stationary noise. And yet realisation and optimisation of this control system is fundamental to Advanced LIGO achieving and maintaining sufficient sensitivity to be able to detect gravitational waves. Such a complex challenge is in need of a modern solution such as the application of Machine Learning/AI algorithms but a mature solution to this problem is yet to be demonstrated. In this project you will get to work with experts in both Machine Learning and gravitational wave detector instrumentation and have a unique opportunity to bring together knowledge from both fields into a practical demonstration of Machine Learning control of a suspended laser interferometer which is hardware compatibility with the Advanced LIGO detectors. Candidate should have a strong interest in learning about ML/AI algorithms and a strong foundation in coding in Python and would ideally have practical experimental skills or a willingness to learn these skills during the course of this project.
2. Seismic Isolation System Commissioning for Gravitational Wave Detector Prototype Facilities:
Seismic Isolation Systems are a vital for gravitational wave detectors to reach observational sensitivity and just as vital for prototype scale facilities (such as the Glasgow Interferometer Facility and the planned LIGO India 10m project). These prototype facilities are vital for the development and demonstration of technology for future detectors, and they are just as vital for the training of future LIGO operators, scientists and engineers. In this project the successful candidate will complete a seismic noise study of the prototype facility in Glasgow and of the existing passive seismic isolation platforms inside the vacuum system. The candidate will also take a role in designing a new improved active seismic isolation platform system, taking the existing conceptual design to final prototype stage and take a lead role in building the system in the Glasgow 10m prototype vacuum facility. You will be supported in completing this work by the Glasgow team of postdoctoral research scientists and mechanical and electrical engineers. In undertaking this project, you will gain valuable front-line experience of working on gravitational wave detector instrumentation using LIGO standard control and data acquisition hardware and LIGO suspension and seismic isolation technology, this project is ideally suited to a candidate with a strong interest in experimental physics and a future career working on the LIGO detectors or similar projects.
Please apply by reading through the necessary information on the postgraduate study website.
Cardiff University:
- Utilizing Machine Learning for Environmental Adaptation in Gravitational Wave Detector
Gravitational wave (GW) detectors are large-scale Michelson interferometers. They detect distortions in space-time caused by astrophysical GWs as the phase difference of two laser beams traveling along the interferometer arms. Because these space-time distortions are extremely small—typically on the order of 10^(−21) meters—GW detectors are incredibly sensitive instruments, operating at the precision limits set by Heisenberg’s uncertainty principle. Achieving such ultimate sensitivity involves a multitude of state-of-the-art technologies. To operate such a highly complex system stably, numerous control loops are employed at various levels, from local seismic isolation systems to the global control of interferometer operations. Because feedback controls typically assume linear plants, it is challenging to characterize noise coupling from the environment (such as temperature fluctuations, winds, and electromagnetic emissions), which often involves highly nonlinear processes. Additionally, there are numerous potential noise sources that can affect the operational status. In this project, we will employ machine learning techniques to understand how environmental conditions impact interferometer stability and sensitivity. The ultimate goal is to adjust some of the feedback loops to improve the duty factor of the interferometer.
Supervisory team: Dr. Keiko Kokeyama in collaboration with Dr.Mayank Chaturvedi and Dr. Subhamoy Chakraborty
Contact details: Gravity Exploration Institute, Cardiff University. kokeyamak@cardiff.ac.uk
The fees for 2024 intake are £28,200. For 2025, fees will be bit higher. Please check Cardiff-India Scholarship for scholarships workshop.