Research Assistant (Topological Data Analysis)

Join Our Team at the School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore

The School of Physical and Mathematical Sciences (SPMS) at NTU Singapore hosts research and education activities in two divisions: Division of Mathematical Sciences (MAS) and Division of Physics and Applied Physics (PAP). MAS covers diverse topics ranging from pure mathematics to the applications of mathematics in cryptography, computing, business, and finance. PAP covers many areas of fundamental and applied physics, including quantum information, condensed matter physics, biophysics, and photonics. Over the years, SPMS has attracted talented individuals from around the world and Singapore to join as scientific leaders and researchers.

We are looking for a highly motivated Research Assistant to join Associate Professor Xia Kelin's team at the School of Physical and Mathematical Sciences. The project focuses on developing topological data analysis (TDA) techniques, such as persistent homology, and applying these methods to real-world data, including biomolecular datasets.

Key Responsibilities:

• Contribute to the development and implementation of topological data analysis (TDA) techniques such as persistent homology, with application in real data sets such as biomolecular data and network data

• Perform data preprocessing, feature extraction, and analysis on large datasets

• Preparation of research papers, reports, and presentations to disseminate findings

• Participate in regular team meetings and contribute to the overall progress of the project

Job Requirements:

• Bachelor’s degree in applied mathematics or related areas, with a strong background in topological data analysis (TDA) and machine learning on biomolecular data

• Experience with biomolecular data, particularly protein, DNA, and RNA data, knowledge of structural biology and protein modeling preferred

• Proficiency in programming languages such as Python, R, or similar

• Excellent analytical and problem-solving skills

• Ability to work both independently and collaboratively in a team

• Previous research experience and publication record in a related field preferred

The College of Science seeks a diverse and inclusive workforce and is committed to equality of opportunity. We welcome applications from all and recruit on the basis of merit, regardless of age, race, gender, religion, marital status and family responsibilities, or disability.

We regret to inform that only shortlisted candidates will be notified.