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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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., Python, PyTorch/TensorFlow, C/C++ as appropriate) and experience with large-scale data analysis. Demonstrated ability to develop novel AI methods and adapt them to complex scientific problems. Ability
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– particularly in battery fire combustion and spread. Strong skills in turbulence modelling, CFD mesh generation in complex 3D geometries. Proficient in handling large data sets and the ability to analysis and
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, MATLAB and R • Experience in spatial analysis • Experience in using large-scale data sets • Have strong publication records • Excellent scientific writing and communication skills More
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computing (HPC) for large-scale data analysis. Experience with seismic tomography, full-waveform inversion, or other advanced imaging techniques. Familiarity with modern data processing workflows and software
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. This position focuses on the development and application of large language models (LLMs) for advancing food informatics, food bioactives research, and sustainable food innovation. The selected fellow
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ignition, flame spread, gas release, and jet/fire dynamics in battery systems. • Collaborate with experimental teams to validate models against laboratory-scale and large-scale fire tests
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profiling and artificial intelligence. The successful candidate will lead efforts to generate and analyze genome-wide data that capture how editing enzymes interact with DNA in various chromatin and cellular
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input and supervision. Lead the development of evaluation framework and/or assessment tool, survey design, interview, focus group discussion, qualitative and quantitative data analysis, and data
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toolkits for real-time surveillance of genomic data by integrating climate and mosquito vector factors to support environmental and public health responses. Collaborating Team ● Environmental Health