58 optimization Fellowship research jobs at Nanyang Technological University in Singapore
Sort by
Refine Your Search
-
and development in the chemical conversion and valorization of hazardous waste streams, focusing on complex, reactive materials. Involves process design, optimization, and scale-up, including reaction
-
optimization of multi-modal LLMs. Investigate and implement methodologies to ensure AI authenticity, accountability, and the integrity of digital content. Develop and refine machine learning and deep learning
-
Materials, Bioinspired Materials and Sustainable Materials. We are looking for a research fellow with a strong background in electrochemistry and catalysis to Development and optimization of biomass chemical
-
solid particle transport. The successful candidate will contribute to the creation of an AI-optimized platform capable of achieving up to 50× speedups in simulation performance, enabling real-time, energy
-
the prototyping of sensor devices and contribute to the optimization of fabrication processes. Maintenance of lab or equipment or supplies that include procurement and liaison with suppliers. Assist or produce high
-
offers a unique opportunity to drive high-impact research in a collaborative and innovative scientific environment. Key Responsibilities: Contribute to the development and optimization of protein
-
development and optimization of plasma-based PVD and CVD processes for advanced material applications. Operate and maintain semiconductor analysis and metrology tools to evaluate thin film and device properties
-
characterize plasma process equipment. Familiar with COMSOL software to simulate the influence of magnetic field on plasma flow. Conducts various design simulations to refine processes. Optimize vacuum coating
-
plasma process equipment. Characterize the influence of magnetic field on plasma flow. Conducts various design experiments to refine processes. Optimize vacuum coating processes, and leading R&D efforts in
-
Responsibilities: Conduct programming and software development for graph data management. Design and implement machine learning models for optimizing graph data management. Conduct experiments and evaluations