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Field
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opportunity to develop cutting-edge AI-enhanced algorithms for analyzing transposable elements (TEs) in cancer epigenomics, with direct translational applications to precision oncology and immunotherapy
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Project Overview The DiSTAP programme addresses deep problems in food production in Singapore and the world by developing a suite of impactful and novel analytical, genetic and biosynthetic
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in the Phi_Lab, led by Dr. Azeem Ahmad, and will focus on the development of advanced reconstruction algorithms and next-generation quantitative optical microscopy and tomography systems for imaging
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develop throughput-optimal entanglement distribution algorithms (both centralized and decentralized algorithms) for quantum networks with resource constraints. The project is funded by the EPSRC AI hub
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genomic graphs. The project will also deliver efficient algorithms to train these models under budget and time constraints, facilitating flexible adoption of the methods. The project is carried out in close
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guiding new mathematical and algorithmic developments. A Ph.D. in mathematics, physics, computer science, or a closely related area is required. To be considered for the initial review, with an intended
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develop throughput-optimal entanglement distribution algorithms (both centralized and decentralized algorithms) for quantum networks with resource constraints. The project is funded by the EPSRC AI hub
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learning, and AI-driven manipulation. This position offers the opportunity to work on real-world robotic systems and develop novel algorithms at the intersection of robot learning, control, and AI
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region of Portugal, although other tasks may be considered according to the profile of the recruited researcher. The researcher will be responsible for implementing spatial analysis algorithms, developing
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of Physics and Technology . The position will be hosted in the Phi_Lab, led by Dr. Azeem Ahmad, and will focus on the development of advanced reconstruction algorithms and next-generation quantitative optical