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 a Project 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.