Project Officer (Nanomaterials)

Nanyang Technological University Singapore; Singapore; On-site; SGD 60,000 - 90,000; Full time

Job summary

NTU Singapore's IDMxS seeks a Project Officer to help develop machine learning–driven nanosensors. You will design and functionalize nanoparticles with receptor ligands, perform spectroscopic measurements including SERS, and build a database of receptor–analyte data.

You will apply in silico calculations such as DFT, contribute to data analysis and ML frameworks to optimize receptor choices, and assist in preparing research outputs.

Qualifications

• Bachelor's degree in chemistry, materials science or related discipline.
• 3+ years of relevant research experience in nanomaterial synthesis or sensing.
• Experience with spectroscopic techniques, especially SERS.
• Familiarity with computational approaches like DFT simulations.
• Familiarity with machine learning applied to spectroscopic data.
• Good communication skills in an interdisciplinary setting.

Responsibilities

• Design and functionalize nanoparticles with receptor ligands for nanosensing.
• Perform spectroscopic measurements including SERS to study interactions.
• Build a spectroscopic database across receptor–analyte pairs.
• Analyze spectroscopic data and interpret results.
• Explore receptor–analyte interactions with in silico calculations (DFT).
• Apply ML to evaluate and optimize receptor combinations for tasks.

Skills

SERS spectroscopy

Nanoparticle synthesis

Spectroscopic data analysis

DFT simulations

Machine learning

Interdisciplinary collaboration

Education

Bachelor's degree in chemistry, materials science, or related discipline

Tools

SERS instrumentation

DFT software

Job description

The Institute for Digital Molecular Analytics and Science (IDMxS), officially launched on 1 December 2022, is a Research Centre of Excellence (RCE) supported by a total investment of around S$160 million over 10 years. The key objective is to support efforts on interfacing the biological and living world with the world of information technology and data science. For more details, please view https://idmxs.org/.

We are looking for aProject Officer (PO) to support the development of machine learning-driven, array-based nanosensors for detecting and differentiating complex, multi-component mixtures. The role will focus on the design and fabrication of receptor-functionalized nanoparticles, the collection and analysis of spectroscopic data across multiple receptor-analyte pairs, the investigation of underlying receptor-analyte interactions, and the development of suitable machine learning frameworks for the selection and optimization of receptor combinations for different analytical tasks.

Key Responsibilities:

• Design and functionalize nanoparticles with different molecular receptors for array-based nanosensing.
• Perform spectroscopic measurements, including surface-enhanced Raman scattering (SERS), to investigate receptor-analyte interactions.
• Establish a spectroscopic database comprising measurements across multiple receptor-analyte pairs.
• Perform data processing, analysis, and interpretation of spectroscopic measurements.
• Investigate underlying receptor-analyte interactions with the aid of in silico calculations, including density functional theory (DFT) simulations.
• Apply machine learning approaches to evaluate, select, and optimize receptor combinations for different analytical tasks.
• Assist the Principal Investigator with the preparation of research papers and other scientific outputs.

Requirements:

• Bachelor’s degree in chemistry, materials science, or a related discipline.
• Min 3 years of relevant research experience in nanomaterial synthesis, characterization, surface functionalization, and/or applications in molecular sensing.
• Experience with spectroscopic techniques, particularly surface-enhanced Raman spectroscopy, including the analysis and interpretation of spectroscopic data.
• Familiarity with computational approaches for investigating molecular interactions, such as density functional theory (DFT) simulations.
• Familiarity with machine learning approaches applied to spectroscopic datasets.
• Good communication skills, with the ability to work effectively in an interdisciplinary research environment.

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

Hiring Institution: NTU