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for Sustainable proteins, who will be assessing in parallel the protein digestibility, bio accessibility and bioavailability of alternative proteins Key Responsibilities: To carry out analytical biochemical
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), Singapore, is a multidisciplinary institute committed to developing new paradigms for biomedical research by focusing on the quantitative analysis of dynamic functional processes. Through quantitative
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Genetic Studies: Support studies on genetic variants affecting drug metabolism, particularly those relevant to Asian populations. Work with bioinformatics and clinical collaborators to interpret
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part of a larger network, undergo persistent changes that ultimately lead to experience-dependent rewiring of the brain. In parallel to understanding how memories are formed, we are also keen to
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: Proficiency in Python, PyTorch, JAX, or other ML frameworks - Computing: Experience with large-scale datasets, parallel computing, and GPUs/TPUs. - Algorithm Development: Ability to develop and optimize Machine
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://discovery.nus.edu.sg/5460-catherine-w-m-ong Main Duties and Responsibilities The Research Fellow will design and execute experiments in M. tuberculosis infection of mice, processing of samples, and associated readouts
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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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Familiarity with research methodologies and ethical guidelines related to clinical and animal studies Proficiency in multi-omics data analysis, and bioinformatics, preferably preferred Excellent organizational
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on experimental techniques and methodologies. Desirable Skills and Experience Experience with bioinformatics tools for RNA sequencing data analysis. Knowledge of immune responses to viral RNA and cellular stress
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expertise in biostatistics, bioinformatics, or computational biology. The successful candidate will join a dynamic and interdisciplinary team focusing on the development and application of novel statistical