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evaluated to determine whether they provide additional haemodynamic information beyond conventional Doppler methods. To provide mechanistic insight into the experimental findings, computational fluid dynamics
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computational chemistry, reaction network analysis, and machine learning for organometallic catalytic reactions. 2. Design of membrane-permeable macrocyclic peptide drugs via machine learning structure
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to evaluate powder bed behaviour, melt pool dynamics, and inter-material transition zones, assessing their impact on process stability, densification, and component performance. Analyse experimental and
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models, with the help of our Engineered Mouse Model Core Facility. Evaluate transcriptome perturbations using next-gen sequencing analysis, RT-PCR, and qPCR. Characterize mouse neurodevelopmental
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join a dynamic and collaborative team engaged in large-scale, externally funded projects addressing pressing urban challenges in Singapore and globally. The positions offer a supportive research
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in space applications are usually not radiation-hardened and thus require dedicated test campaigns and complex radiation analysis. The research activity relates to the preparation of radiation test
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mechanisms, biomarkers, and therapeutic targets in solid tumors through multi-omics data analysis of large pan-cancer datasets, including proteogenomic data generated across high-throughput profiling platforms
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30th September 2026 Languages English English Norsk Nynorsk English PhD Research Fellow in climate data analysis and machine learning emulation of hydrological models Apply for this job See
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identification through lab-scale and field experiments. Key Responsibilities: Develop algorithms for guided-wave analysis, response analysis, sensor fusion, and system identification using distributed and multi
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and behaviour. With state-of-the-art MRI, PET, and EEG facilities, the CNS provides a dynamic environment for investigating the neurobiological mechanisms underlying mental health and the effects