Research Associate (Mathematics)

NATIONAL UNIVERSITY OF SINGAPORE; Pasir Panjang; On-site; MYR 100,000 - 150,000; Full time

Job summary

A leading academic institution in Malaysia is seeking a candidate for a data-driven research position in machine learning. The successful candidate will assist in model development and manage datasets while collaborating with researchers. A Master’s degree in a relevant field and proficiency in Python are required. This role offers an opportunity to engage in innovative research projects with significant academic impact.

Qualifications

• Master’s degree or above in Data Science, Statistics, Mathematics, or a related discipline.
• Strong academic background in machine learning or quantitative analysis.

Responsibilities

• Assist in the design, development, and evaluation of machine learning models.
• Collect, clean, and manage datasets from various sources.
• Conduct literature reviews and benchmarking experiments.
• Implement data pipelines and model evaluation frameworks.
• Prepare research reports and documentation.

Skills

Python proficiency

Machine learning libraries

Deep learning framework experience

Data preprocessing

Good communication skills

Education

Master’s degree in Data Science, Statistics, or related discipline

Tools

NumPy

Pandas

scikit-learn

PyTorch

TensorFlow

Job description

Interested applicants are invited to apply directly at the NUS Career Portal

Your application will be processed only if you apply via NUS Career Portal

We regret that only shortlisted candidates will be notified.

Job Description

The successful candidate will work with Professor Delin CHU on data-driven research in the field of machine learning and applied data science under a project on "Regularization and Stabilization of Port-Hamiltonian Descriptor Systems".

The main responsibilities of the position include:
1. Assisting in the design, development, and evaluation of machine learning models;
2. Collecting, cleaning, and managing datasets from various sources;
3. Conducting literature reviews and benchmarking experiments;
4. Implementing data pipelines and model evaluation frameworks;
5. Preparing research reports, documentation, and presentation materials;
6. Collaborating with other researchers and supporting academic publications.

Qualifications / Discipline:
1. Master’s degree or above in Data Science, Statistics, Mathematics, or a related discipline;
2. Strong academic background in machine learning, algorithm design, or quantitative analysis.

Skills:
1. Proficient in Python; familiarity with data science libraries such as NumPy, Pandas, scikit-learn, and visualization tools (e.g., matplotlib, seaborn);
2. Experience with at least one deep learning framework (e.g., PyTorch, TensorFlow);
3. Familiarity with data preprocessing, feature engineering, and model evaluation techniques;
4. Ability to manage and analyze large datasets (structured and unstructured);
5. Good communication skills, attention to detail, and ability to work both independently and collaboratively.

Experience:
1. Prior exposure to academic research, internships, or industry projects involving data analysis or machine learning;
2. Experience with any of the following is advantages: natural language processing, computer vision, time-series analysis, or multimodal data integration;
3. Experience preparing reports, presentations, or contributing to academic work during research projects.