128 parallel-processing-bioinformatics Fellowship positions at Nanyang Technological University in Singapore
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guidelines related to clinical and animal studies Proficiency in multi-omics data analysis, and bioinformatics, preferably preferred Excellent organizational skills, attention to detail, and the ability
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Strong foundation in CFD, Programming proficiency such as Python, AI/ML techniques, Experience with parallel computing on CPU/GPU cluster, use of CUDA, MPI is a plus. Experience Experience with open-source
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gnotobiotic studies and microbiome analysis/bioinformatics. Key Competencies/Requirements: Hold a doctoral (PhD) degree in neuroscience or relevant disciplines with strong publication track record Lead
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for multiple-CPU and/or GPU platforms via parallelization schemes. Validating these codes via canonical and real-world examples. Job Requirements: PhD in Electrical and Electronic Engineering, Applied
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Responsibilities: Development of design rules for 3D printed parts that are fabricated by various additive manufacturing (AM) and hybrid manufacturing processes. Development of analytic models, simulation, and
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of design rules for 3D printed parts that are fabricated by various additive manufacturing (AM) and hybrid manufacturing processes. Development of analytic models, simulation, and optimization for the AM
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model is employed to forecast renewable energy availability, providing crucial insights for the design optimization process. The ML-assisted operation tackles the dynamic optimization of parallel energy
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foundry on the development of CMOS frontend wafer, and back-end-of -line integration process. To carry out ReRAM electrical transport measurement using probe station, or on bonded memory chip, and able
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on rapid and accurate quantification of disasters using remote sensing and space geodesy. They will also advance InSAR processing algorithms to optimise change detection capability in Southeast Asia, where
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Circuit Boards. More precisely, it will focus on developing an efficient processing route to dismantle efficiently as well as sort resulting electronic components into fraction as enriched as possible in