58 combinatorial-optimization Fellowship positions at Nanyang Technological University
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learning, large-scale model optimization, and generalization. To explore scalable optimization methods for large-scale, distributed, and multi-node collaborative training. To conduct theoretical analysis
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research on shipping and port operational optimization, maritime decarbonization, data analytics, and the development and application of novel methodologies (including LLM-based prediction and optimization
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, and optimize multimaterial LPBF processes, integrating in-situ monitoring, process parameters, material combinations, and resulting microstructural and structural outcomes. Design and optimize
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for Science with inadequate attention and support. This proposal addresses the gap by focusing on the development of optimized implementations for AI for Science workloads. Bespoke communication and computation
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implement VLA models and world models. Develop and optimize deep learning algorithms to enable robotic arms to perform complex tasks guided by natural language instructions. Utilize PyTorch to train and fine
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development, operation and optimization of plasma devices and associated diagnostics. Experience or exposure to plasma diagnostics. Strong written and verbal communication skills with demonstrated ability
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of spintronic THz source activated selectively in an arbitrary spatial pattern using spatial light modulators. Methodology: involves working on three integrated verticals: (i) Optimization of FM/HM
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accelerators for problems that are not efficiently handled by digital systems, such as AI training, real-time optimization, etc. Key Responsibilities: Defining detailed experimental steps. Conducting experiments
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platforms, including robotic systems, laboratory automation, and AI/machine learning-assisted approaches for experimental design, optimization, and materials discovery. The research will target advanced
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on the design, formulation and evaluation of stimuli-responsive nanoparticles to enhance RNA delivery and endosomal escape. Key Responsibilities: Develop and optimize stimuli-responsive nanoparticle formulations