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, biologists, and engineers. You will also have the opportunity to present your research at international conferences, expanding your network and gaining valuable experience in scientific communication
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variants of importance sampling. We will connect these methods to modern formulations of Monte Carlo algorithms to improve their accuracy, scalability, and overall computational cost. The methodology so
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seminars and events, alongside our Doctoral Researchers Core Development programme (transferable skills training), provide those studying a research degree with a wealth of social and networking
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computational modelling to be used to design and re-engineer flower architecture. The RA's main focus will be on computational modelling of gene regulatory networks for predicting the mechanisms leading
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challenging properties of uncertainty, irregularity and mixed-modality. It will examine a range of models and techniques that go beyond Markovian approaches, including state-space models, tensor networks, and
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computational modelling to be used to design and re-engineer flower architecture. The RA's main focus will be on computational modelling of gene regulatory networks for predicting the mechanisms leading
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organizes seminars, workshops, and summer schools that will help the PhD students grow their network and skills. School of Engineering and School of Chemical Engineering are two of the six schools of Aalto
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The funding provider: Health Data Research UK Subject areas: Wider Data Science Field, Maths and Computer Science Project start dates: 1st October 2025 ** (Please see the note below regarding
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mixed-modality. It will examine a range of models and techniques that go beyond Markovian approaches, including state-space models, tensor networks, and machine learning frameworks such as recurrent
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for these architectures. This will also guide hardware design for such devices and tackle crucial challenges in networked systems and entanglement transmission. Candidate’s profile Knowledge of quantum computing and an