483 systems-science-"https:" "https:" "https:" "https:" "UCL" Fellowship research jobs in Singapore
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to maintain excellence in research in mathematics and computer science. Skilled research staff working at this frontier research field is an essential human resource towards generating new knowledge and
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, neurodegenerative disorders, telomere biology, and genome function. SBS is home to a vibrant, international community of scientific leaders, researchers, and professionals dedicated to innovation, discovery, and
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understanding of emerging infections through world-class research that integrates immunology, infection biology, pathogen genomics, and computational approaches. This integration drives comprehensive studies
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, Bioengineering, Applied Physics, Engineering Physics/Science, or related field. Hands-on experience in microfluidics, MEMS, biosensing, or bioreactor design. Knowledge of cell culture systems, organoids, or tissue
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Posting Start Date: 23/03/2026 Job Description The Saw Swee Hock School of Public Health (SSHSPH) at the National University of Singapore (NUS) is seeking multiple determined full-time Research Fellow
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● PhD (or Master’s with strong relevant experience) in Bioinformatics or a related discipline (Neurobiology, Computer Science, Statistics, Epidemiology, Systems Biology, Computational Biology
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faculty specialising in Biostatistics, Bioinformatics, Systems Biology, Artificial Intelligence (AI), and other quantitative and data-driven sciences. CBDS functions as a strategic platform for cutting-edge
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invites applications for a Research Fellow to play a key role in advancing translational projects in molecular and spatial biology. This full-time research role is ideal for early-career researcher seeking
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Environmental Engineering. The Research Fellow is expected to: • Conduct novel and impactful research. • Assist in the design of and lead experimental activities within the lab. • Disseminate research
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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