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mechanotherapeutics. 4. Neuromechanobiology: this area focuses on discovering the mechanobiological basis of neurons, neural networks, and the brain in memory, learning, cognitive function in health and
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building automated systems or ML pipelines – 15% Demonstrated experience implementing structured, scalable, or automated software systems. Evidence of experience with neural networks, LLMs, or training
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laser’, through the neural-network control of a tiled array of fibre lasers in a coherent beam combination architecture, for unlocking novel scaling and beam shaping capabilities in real-time. You will
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to design new learning frameworks and neural network architectures to advance our fundamental understanding of how the human brain forms perception and memories. In detail, you will use transformer
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advanced light microscopy data. The lab’s research scope ranges from reinforcement learning for drug design, interpretable ML pipelines for cancer research and diagnosis as well as graph neural networks
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if you are highly motivated, have interests in computer vision and neural networks, and want to both contribute to new advances in a field with real world applications. Your research focus will be
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Computer Engineering. More information on the laboratory is available at www.neuroimaginglab.org . The MNNDL group at NUS is a multidisciplinary team studying the human neural bases of cognitive functions
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candidates/candidates who are in the closing stages of their master’s degree can also apply Solid background in artificial intelligence and machine learning, including deep neural networks Programming
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decision agents based on graph neural network or similar will an advantage. Key Competencies Good knowledge in reliability analysis. Experience in FMECA and equipment health management will be advantageous
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applications of neural networks to the analysis of multi-omic data, models for predicting phenotypes using genotype data, biological data integration, etc.. Participation in these projects will include