Data Analysis and Machine Learning for Direct Dark Matter Detection and Neutrino Physics

analysis and statistical methods for direct detection of dark matter and astroparticle neutrino measurements Analysis of data from the XENONnT liquid xenon time projection chamber, including signal reconstruction, detector response modelling, and background characterisation Quantum and mechanical sensing approaches to dark matter detection, including analysis pipelines for levitated or mechanical sensor experiments Machine learning methods for physics inference, such as simulation-based inference, normalising flows, and fast surrogate models of detector physics Phenomenology of dark matter direct detection, including modelling of quantum sensing approaches for direct detection or projection of the sensitivity of next-generation experiments. Important Note The topics listed above are not exhaustive. Prospective PhD candidates are welcome to propose their own research ideas. Candidates are strongly encouraged to contact potential supervisors at least 3 months before the application deadline, as the process of identifying a suitable supervisor and preparing a research proposal may require time. When you email Assistant Professor Qin Juehang, please: Introduce yourself and send your curriculum vitae Share about your academic background Provide information on your research interests and how it is aligned with this project And how you hope to achieve your PhD aspirations Minimum Entry Requirement A Bachelor's degree with honours at least at Second Class Upper level, Master's degree in the relevant areas and the ability to pursue research in the candidate's proposed field of advanced study. Shortlisted applicants will undergo an interview session as part of the selection process. A valid GRE score is required for applicants who are not graduates of the Autonomous Universities in Singapore. See detailed requirements for English language on competency and GRE requirements here. Funding Notes Prestigious scholarships offered by the Nanyang Technological University, Singapore (NTU Singapore) allows outstanding PhD students to pursue their research endeavours at a world-class university. At NTU, we recognize academic excellence and research potential that will help you focus on making groundbreaking discoveries in your field.