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. Responsibility: * Develop or integrate novel statistical methods and algorithms for analyzing large-scale -omics data, including gene regulatory network inference, cell lineage reconstruction, multi-dimensional
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the ranking. However, STV method becomes considerably more complex with encrypted ballots. Our goal is to develop an algorithm/protocol to count encrypted ballot using the STV method. Our first point of
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? As a PhD Candidate, you will develop innovative methods for predicting and reducing the energy consumption of large-scale AI systems during their design phase. Your work will help shape environmentally
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needs. By bridging human-centric innovation, generative algorithms, and sustainability metrics, this project seeks to redefine how novel products and systems are conceived, developed, and evaluated. You
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, and space hardware. This PhD research aims to develop a comprehensive Mode Selection Framework for Reduced Order Modelling (ROM) in Structural Dynamics—using machine learning to build robust
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focus will be on developing compact, efficient, and real-time LLM algorithms/hardware on the edge and developing demos for specific applications such as speech disorder therapy. Your responsibilities will
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) uses principles from systems neuroscience to develop reliable, low-power spiking neural networks and learning algorithms for implementation in a new generation of neuromorphic hardware. Both projects
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This doctoral research will focus on the development, optimisation, and coordinated deployment of advanced aerial platforms, specifically electric vertical take-off and landing vehicles (eVTOLs) and
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for Robotic and Autonomous Perception This project aims to make robotic perception systems safer and more reliable by developing new techniques that continuously monitor the performance of their machine
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experimentation with Asst. Prof. Eli N. Weinstein. Your goal will be to develop fundamental algorithmic techniques to overcome critical bottlenecks on data scale and quality, enabling scientists to gather vastly