434 algorithm-development-"Multiple"-"Prof"-"Prof"-"Simons-Foundation" "U.S" PhD positions in United Kingdom
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of Dr Jing Ren at the MRC Laboratory of Molecular Biology (Cambridge, U.K.) to map the serotonin circuit development by tissue clearing and expansion microscopy. The serotonin (5-HT) system is essential
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third over the past 25 years, which is inferred from sparse soil data and the widespread decline of their avian predators. Recent developments in soil geophones and contact microphones have enabled
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specifically on tumour metabolic targets. You will develop and support the INSTINCT-MB. programme through the provision of experimental, analytical and bioinformatic expertise. This will include the development
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perspectives on health and wellbeing and in turn, developing new solutions to address wider societal and political challenges on ageing populations; community cohesion; and generational divisions. We welcome
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increase healthcare access. Further, such technologies can facilitate remote training monitoring and performance enhancement for athletes. Developing accurate, low-cost, comfortable technologies
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. Developing and maintaining knowledge of relevant research findings and policy/practice developments. Collaboratively working to prepare research outcomes for submission to high-quality refereed journals and
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dynamics and tissue morphogenesis during embryo development using cellular, molecular and mechanical approaches. Cell movements underlie tissue patterns and shapes. Using chick embryos as the model system
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The overarching aim of the project is to understand how early neurodevelopmental risk factors disrupt brain maturation and contribute to psychosis vulnerability across development. This PhD project
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the development and implementation of machine learning (ML), computer vision (CV), large language models (LLMs), and vision-language models (VLM) to automate data extraction and interpretation for productivity
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this issue and we could use obtain data-driven models using machine learning algorithms such as artificial neural networks, reinforcement learning, and deep learning. A typical caveat of data-driven modelling