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Job Description We are looking for a Research Fellow under the National University of Singapore (NUS) to support a project investigating the fundamental theoretical and algorithmic performance
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methods for additive manufacturing applications, including ANNs and evolutionary genetic algorithms for process optimization supported by programming knowledge (e.g. Matlab, Python). Hands-on experience
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to evolutionary time scales. One of the goals of the SCINet Initiative is to develop and apply new technologies, including AI and machine learning (ML), to help solve complex agricultural problems that also depend
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on a project in the area of cross-border electricity market. The role will focus on cross-border electricity market design, market risk analysis, bidding strategies, and relevant optimization algorithms
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by applying existing and novel computational biology, bioinformatic, and machine learning algorithms to sequencing datasets and correlating them with multi-dimensional clinical datasets that contain