136 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" research jobs at National University of Singapore in Singapore
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teaching statements, and at least three letters of recommendation. More information about the university and the department can be found at https://www.nus.edu.sg . Application Materials Required: Submit
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for a talented and motivated postdoctoral fellow to join the Genome Re-InnovaTion Lab (https://grit-lab.org), part of the Synthetic Biology Translational Research Programme at the National University
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storage materials, and employing machine learning and high throughput for the discovery of new electrode materials and electrolyte systems. 1. Holds a PhD degree in chemical engineering, chemistry
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international law. More on CIL can be found here: https://cil.nus.edu.sg/ About the Oceans Law and Policy Team: Ocean Law & Policy is one of CIL’s core programme areas and was established over 10 years ago. It
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insights from cutting-edge clinical and translational research. More information on the Department’s research portfolio may be obtained from https://medicine.nus.edu.sg/obgyn/. The Core Support Faculty will
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interests and goals at https://Singaporebrainhealth.org. The Principal Investigator prioritizes teaching (e.g., meets with team members regularly), rigorous methodology, and active collaborations within and
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role in designing composites materials using inorganic solid electrolytes using computational modelling and machine learning. Qualifications • Ph.D. in Materials Science, Chemistry, Physics, or a
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and interpretable machine learning systems. The successful candidate will work on projects involving ensemble learning, large-scale data analytics, and high-performance model design, aimed at developing
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/ machine learning / statistics on spatial and single-cell omics (transcriptomics, proteomics, epigenomics, metabolomics, meta-transcriptomics, etc.) data. Independently carry out computational and
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enrichment (GO, KEGG), network analysis, genome assembly and binning, systems biology, and multi-omics integration. Apply statistical modelling, machine learning, and deep learning approaches for biomarker