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patients with the genetic disease hereditary hemorrhagic telangiectasia. Approaches make use of spatial omics, advanced imaging techniques such as 3D deep tissue staining, microCT, and synchrotron imaging
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British Sign Language (BSL) into English text. This will involve designing deep learning models that can learn from the available annotated datasets, and also build in a linguistic understanding of BSL. You
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unravel the complex relationships between land use changes and fire regimes over the past 60 years. The successful candidate will lead efforts to: Develop advanced deep learning algorithms for classifying
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Biljecki (National University of Singapore). Your key responsibilities will be: 1. Co-developing the research of work package 1. This work includes, a.o.: Developing deep learning models for the project’s
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familiarity with supercomputing or cloud platforms. Experience with AI/deep learning beyond simple tools (e.g., Random Forest, ANN), particularly in integrating physical models and AI algorithms. Knowledge
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At the heart of SIT’s mission is to nurture industry-ready graduates equipped with deep technical expertise and transferable skills to tackle tomorrow’s challenges. SIT collaborates with industry in
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At the heart of SIT’s mission is to nurture industry-ready graduates equipped with deep technical expertise and transferable skills to tackle tomorrow’s challenges. SIT collaborates with industry in
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the developmental rules underlying phenotypic variation. The successful postdoctoral fellow will develop and implement an empirical framework that utilizes data-driven algorithms to learn relationships between past
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combine ophthalmological, neuroimaging and behavioral data, and incorporate deep learning methods to facilitate biomarker discovery and enhance predictive power. As a postdoctoral associate you will join a
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At the heart of SIT’s mission is to nurture industry-ready graduates equipped with deep technical expertise and transferable skills to tackle tomorrow’s challenges. SIT collaborates with industry in