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Kerja Sepenuh Masa, Research Assistant (Physics) di National University Of Singapore Central Region (Singapore) - Maukerja

Undisclosed

Queenstown, Central Region (Singapore)

Kongsi
Simpan

Lokasi Kerja

  • Queenstown Central Region (Singapore) Singapore

Penerangan Kerja

Tanggungjawab

Job Title: Research Assistant (Physics)
University-Level Unit: Science
Faculty/Department-Level Unit: Physics
Employee Category: Research Staff
Location_ONB: Kent Ridge Campus
Posting Start Date: 20/04/2026

Job Description

The successful candidate will work with Asst. Prof. Marc Hon and Prof. Anthony Tung from the NUS School of Computing on an interdisciplinary NUS Physics × Computing project: AI-Driven Discovery of Dark Matter Candidates via Gravitational Microlensing.


The responsibilities of the position include:

  • Designing methods for anomaly detection in irregularly sampled time-series of stellar brightness over time
  • Physics-aware generation of time-series data containing transient events
  • Coordination with Physics and Computing teams for applications to next-generation astronomical surveys


The role is ideal for someone with a strong computational background combined with an interest in time-domain AI and scientific machine learning. Expertise in astrophysics can be developed during the project.

Qualifications

Bachelor’s Degree in Data Science, Computer Science, Physics, or a similar quantitative field.



Skills:

  • Strong analytical and computational skills in data science, statistical analysis, or machine learning.
  • Proficiency with PyTorch and data analysis frameworks in Python.
  • 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, particularly for time-series data.
  • A record of relevant projects involving temporal data and/or time-series analyses is desirable.

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