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Field
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and wave-equation–based modeling, including familiarity with adjoint-state methods, gradient-based optimization, and multi-scale inversion strategies. Proven expertise in machine learning and deep
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of numerical optimization is an advantage. Experience from high-performance computing is an advantage. Applicants must be able to work independently and in a structured manner and demonstrate good collaborative
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immunophenotyping of colonic tissues. Develop and optimize small animal models of colitis to investigate the mechanistic role of SCFA-producing microbes in mucosal repair. Perform data analysis using computational
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candidates will engage in cutting-edge research under the mentorship of leading experts in one of the following priority research areas: Research area 1: Intelligent Structural Optimization using Physics
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pathogens, such as those causing wheat blast and soybean red leaf blotch. Acquire skills in collecting, processing, and analyzing whole-genome sequence data. Learn to design, develop, and optimize fungal
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will be encouraged to develop thermodynamic interpretations of these mechanisms to optimize their efficiency. Analytical computations, processing and fitting of experimental data, paper writing
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interactions in vitro and in vivo. Here, the work will be devoted to the derivation, characterization and optimization of neural progenitor cells from human induced pluripotent stem cells for in vitro cell
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Singapore’s AI-for-Science ecosystem. Key Responsibilities: The candidate is expected to conduct the following research works Develop and optimize multimodal LLM/MLLMs for downstream tasks (adaptation
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. Key Responsibilities: Develop and run a Cu–Cu hybrid bonding flow for fine-pitch 3D integration. Optimize process windows (pressure/temperature/anneal/surface activation) to minimize contact resistance
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dynamic teams in multi-organizational consortia and carry out research activities focusing on synthesis, characterization and optimization of advanced cathode materials for rechargeable lithium-ion