Sort by
Refine Your Search
-
Listed
-
Program
-
Employer
-
Field
-
, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
-
and testing, process modelling, data processing and reporting, progress report preparation, etc. Journal paper publication. Assistance in research proposal preparation, etc. Assistance in mentoring
-
/ information/ proposal required for research-related grant call process Conduct experiments related to lipids and sporopollenin-based drug delivery Conduct interpretation and application of experimental results
-
lab and outfield studies) Leading in-lab (climatic chamber), outfield data collection and wet laboratory experiments Performing biological sampling (e.g., blood, urine, sweat), sample processing and wet
-
initiatives. Good communication, interpersonal and oral presentation skills. Good polymer science and hollow fiber membrane fabrication and modification background. Good knowledge of membrane processes. Good
-
synthesizing thin-film composite (TFC) hollow fiber membranes Processing and modifying polymeric materials into the design of TFC hollow fiber membranes Characterizing polymeric TFC hollow fiber membranes
-
Responsibilities Development of new machine learning modeling approaches Development of new advanced control and optimization algorithms Optimization of carbon capture process operation Provide regular project
-
domains and formal methods Applying the developed research ideas and approaches to improve the software engineering process in Continental, especially requirement engineering and testing Conducting
-
aspects of computational modelling, brain-computer interface technologies as well as within NUS focusing on design and application from the lens of landscape architecture. The research assistant to be hired
-
and qualified Research Fellow to join our research team on the project titled “Development of 3D Vegetation Quality and Intensity Indices”. This project specifically looks at the processing and