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are demonstrated knowledge related to acoustic modelling, measurement and soundscape. o Essential are demonstrated data analytic skills, ideally with machine learning or statistical modelling • Other general
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Experience using electrochemical and/or flow instrumentation desirable High level analytical capability Ability to communicate complex information clearly Fluency in relevant models, techniques or methods and
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of intelligence, including mathematical and computational models of intelligence, cognitive theories of intelligence, and the neurobiological basis of intelligence. Research and development of new AI or ML
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-omics data to identify therapeutic targets and biomarkers. Study cardiomyopathy across models of diabetes, cancer, and pressure overload. Collaborate in an interdisciplinary team and contribute to high
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diverse classes of inhibitory neurons are specified and integrated into brain circuits during development. Our work bridges developmental neurobiology, disease modeling, and systems neuroscience. To do
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develop AI models to predict and study the tumor evolution and lineages using the multiomic measurements from both bulk, single-cell, and spatial technologies. The lab emphasizes understanding
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algorithms, including machine unlearning techniques, to enhance model robustness and reliability. Design and execute rigorous AI testing frameworks to assess and mitigate risks in AI systems. Collaborate with
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models, and clinical cohorts to uncover mechanisms by which early-life gut microbial metabolism shapes host immunity. We welcome applicants with backgrounds in computational biology, molecular microbiology
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complex patient pathways. The project will consist of three studies: Mapping and modelling of interaction patterns in different patient pathways (e.g. stroke, cancer, elderly care). The objective is to map
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challenges from low carbon shipping and sustainable fuels to solar power technologies and advanced brain models. Learn more at https://mecheng.ucl.ac.uk . Within this dynamic environment, the Moazen Lab is