330 systems-science-"https:"-"https:"-"https:"-"https:"-"UCL" Fellowship positions in Singapore
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The School of Physical and Mathematical Sciences is a center for a broad spectrum of mathematics, pure and applied. There is an opening for a research fellow in the group of Dr. Milind Hegde
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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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systems (MPS) and vascularized organoid platforms to model solid-tumour biology and therapy response. This position will support a project to develop and validate a colon cancer model, a kit-ready
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and artificial intelligence. This exciting position is part of a larger initiative within the NTU College of Computing and Data Science and LKC School of Medicine, where we are pioneering efforts
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research findings and communicate effectively to diverse audiences. More Information Location: Kent Ridge Campus Organization: College of Design and Engineering Department : Materials Science and Engineering
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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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, 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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● 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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, 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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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