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in algorithmic game theory and online learning the opportunity to work with Prof. Celli, developing key skills and gaining access to the research networks of the BIDSA center and the Department
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for the development of the experimental platform, as well as benchmarking new techniques and protocols for implementing quantum algorithms targeting industrially relevant problems ranging from optimisation to quantum
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algorithms. You will work under the overall supervision of Prof Tingting Zhu, Royal Academy of Engineering Research Fellow of the Institute of Biomedical Engineering (IBME) within the Department
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integration; (b) conduct algorithm research and development in areas such as computer vision, multimodal learning and embodied AI; (c) conduct experiments, data collection and performance evaluation; (d
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PhD Studentship: Quantum Algorithms for Nuclear Level Densities Atomic nuclei have a rich structure, with heavy nuclei having many excited states – of order thousands or higher. Knowledge
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how such generalizations can be used to obtain efficient algorithms for geometric intersection graphs. The project will be supervised by prof. Mark de Berg. Information As a PhD student working on
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techniques and machine learning algorithms. The goal is to decipher patterns in the bioelectrical signals. Project UID-50008-2025 funded by FCT-Fundação para a Ciência e a Tecnologia. Scientific Area: Basic
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) experience in large model training, knowledge distillation or efficient deep learning algorithm development, foundation model implementation and optimisation; and (c) good communication skills in English
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conservation related consequences of animal navigation, and (4) links biological and technical systems through models, algorithms, and devices. The acquired knowledge can help to solve major societal questions
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resource. The project will combine algorithm development with hardware-aware modelling and evaluation on FPGA-based platforms. The successful candidate will have the opportunity to help define new approaches