Research Fellow (Statistics and Data Science)

NATIONAL UNIVERSITY OF SINGAPORE; Pasir Panjang; On-site; MYR 60,000 - 80,000; Full time

Job summary

A leading university in Southeast Asia is seeking a PhD-level candidate to work on representation learning and data-assimilation methodologies. The role involves developing complex algorithms, publishing research, and presenting findings at conferences. Candidates should have proficiency in deep learning frameworks and a solid research background. This position offers an opportunity for impactful research in an academic setting.

Qualifications

• PhD in a relevant field.
• Proficient in deep learning frameworks.
• Strong background in statistical modeling and research.

Responsibilities

• Develop methodologies for particle methods in data-assimilation.
• Implement developed methods in practical scenarios.
• Publish research findings in reputable journals.

Skills

Deep learning frameworks (e.g., PyTorch, TensorFlow)

Statistical modeling

Complex algorithms development

Excellent written and verbal communication

Independent research and collaboration

Education

PhD in Machine Learning, Statistics, Signal Processing, Applied Mathematics

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 Assoc Professor Alexandre THIERY on representation learning and high-dimensional time series under a project on particle methods for data-assimilation.

The main responsibilities of the position include:
• Methodology development
• Implementation of the methods
• Publication in journals and conferences
• Presentation of work in conferences

Qualifications

Qualifications / Discipline:

• PhD in Machine Learning, Statistics, Signal Processing, Applied Mathematics, or related fields

Skills:

• Proficiency in deep learning frameworks (e.g., PyTorch, TensorFlow)
• Strong background in statistical modeling and machine learning
• Proven ability to develop and implement complex algorithms
• Excellent written and verbal communication skills
• Capable of conducting independent research and working collaboratively

Experience:

• Published research in top-tier journals and conferences (e.g., NeurIPS, ICML, AISTATS)
• Demonstrated experience in developing novel methodologies in representation learning
• Strong record of presenting at international conferences and workshops