Research Fellow
2 weeks ago
Company description:
The National University of Singapore is the national research university of Singapore. Founded in 1905 as the Straits Settlements and the Federated Malay States Government Medical School, NUS is the oldest higher education institution in Singapore
Job description:
Job Description
The successful candidate will work with Assistant Professor Marc Hon to develop and apply modern machine learning methods for the analysis of large-scale astronomical datasets, emphasizing time-domain astronomy. The research direction can flexibly utilize archival data from major space-based and ground-based observatories, including NASA's Kepler, TESS, and JWST missions, ESA's Gaia mission, and large-scale spectroscopic surveys such as LAMOST. Scientific research directions include—but are not limited to— stellar variability, exoplanets, transient events, and new astrophysical phenomena.
The main responsibilities of the position include:
Conducting original research using large-scale datasets from space-based missions and ground-based surveys.
Developing and applying machine learning and statistical approaches specifically tailored to the analysis of complex astronomical data, with emphasis on time series and multimodal data integration.
Engaging in active collaboration with team members and, where appropriate, contributing to mentoring students or junior researchers involved in related projects.
Qualifications
• Qualifications/ Discipline: PhD in Physics, Data Science, Computer Science, Astronomy, Astrophysics, or a related quantitative discipline.
• Skills:
Strong analytical and computational skills in data science, statistical analysis, or machine learning.
Proficiency with Python and data analysis frameworks.
Familiarity with large, complex datasets and modern computational techniques.
Good written and oral scientific communication skills.
• Experience:
Demonstrated experience conducting independent research involving the analysis of large datasets.
Familiarity with modern machine learning methodologies is strongly desirable.
A publication record demonstrating relevant skills in astronomy, astrophysics, physics, computer science, or related fields
More Information
Location: Kent Ridge Campus
Organization: Faculty of Science
Department : Physics
Job requisition ID : 29918
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