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algorithms and complexity theory, including in both well-established settings (e.g., sequential computation on a single machine and distributed/parallel computation on multiple machines) as well as emerging
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Bayesian approach (Lages, 2024). Techniques used: Computational modelling, Bayesian inference, sampling and simulation techniques, prior distributions and posterior predictive checks, model comparison
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, together with relevant expertise in areas related to Artificial Intelligence, such as: Foundational Models, Algorithmic Research Machine/Deep Learning Computer Vision Parallel & Distributed Computing Control
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Funded PhD studentships The successful candidate for each studentship will receive full funding for tuition and stipend, at UKRI standard levels. International candidates are encouraged to apply
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further studies as a PhD candidate. Additional programme cost: £500 Fugitive methane in Scotland: Plume mapping and isotopic characterisation using Cavity Ring-down Spectrometry (Dr Adrian Bass) Supervisor
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Huntington’s disease, and a preclinical model of schizophrenia. In a parallel program of research, we have been exploring epigenetic inheritance via the paternal lineage. We have discovered the transgenerational
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Professorship - Programme Information (PDF, 123 KB) Recently selected Humboldt Professors Our Alexander von Humboldt Professors for AI WANTED: Alexander von Humboldt Professors (female) The Alexander von Humboldt
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Qualifications Bachelors in Computer Science or STEM field required. Master/PhD degree in STEM field preferred 3 - 5 years of IT related experience Exceptionally strong background in Linux/Unix Experience with a
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optimisation, distributed-parallel-GPU optimisation (e.g. pagmo2), Taylor-based numerical integration of ODEs (e.g. heyoka), differential algebra and high order automated differentiation (audi), quantum