Sort by
Refine Your Search
-
Listed
-
Employer
-
Field
-
outputs across Projects 3-1 and 3-2 Manage and process large sets of operational data for case study analysis Contribute expertise in power grid optimisation to enhance planning models Participate in
-
, Yong Loo Lin School of Medicine at the National University of Singapore (NUS) is seeking a motivated and experienced Research Fellow (RF) or Research Associate (RAssoc) to join our dynamic team in
-
research. Qualifications The selection process will be on a rolling basis until the position is filled. Start date is flexible but the successful candidate should ideally commence no later than 15 November
-
change without prior notice. Application Process Please submit the following documents in one (combined) PDF and attach it under the CV column in the system: Curriculum Vitae (maximum of 3 single-spaced
-
required to give seminar(s). You are also required to acknowledge ARI in all your publications resulting from the period you are at the Institute. Application Process Please submit all documents in one
-
framework on how to build up a generic framework to use learning-assisted approach to solve various optimization problems Develop mathematical modeling framework to find the optimal operation strategy Conduct
-
data collection with stakeholders from participating schools, organize, and manage data storage (f) Process and conduct qualitative data analysis (i.e., transcribing, coding) (g) Write reports, be
-
) The Centre for Quantum Technologies (CQT) in Singapore brings together physicists, computer scientists and engineers to do basic research on quantum physics and to build devices based on quantum phenomena
-
including key components such as cell configurations, flow channels, electrodes, membranes, and catalysts for HER and other electrochemical processes. • Conduct CFD and electrochemical simulations
-
against existing commercial technologies. Key Responsibilities: Perform literature review on data available for commercial processes Provide estimations for data not available in literature Develop process