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Research theme: Formal Methods How many positions: 1 This 3.5 year PhD is funded by the Department of Computer Science at The University of Manchester. The successful candidate will receive
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, data science using EHRs, machine learning, data mining, and natural language processing are preferred. Job Description: Develop large language models and other methods and tools to effectively use
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financial barriers to achieving theoretically optimal city sizes using qualitative methods, including stakeholder interviews and policy analysis. Integrating Theory into Dynamic Models Embed the sustainable
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least one of the following areas: formal methods, machine learning. Additional knowledge and experience within the following areas are appreciated: formal verification, deep learning, dynamical systems
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Reasoning about Automated Reasoning'. From a fundamental research perspective, this relates to the automation of meta-reasoning pertaining to general-purpose reasoning methods. Here, the intended focus is on
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Profile: We seek someone with strong mathematical maturity in control theory, dynamical systems, or applied mathematics. Familiarity with nonlinear systems analysis, graph theory, and formal methods (e.g
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international backgrounds, BIPS’s research covers the full spectrum from methods development and identification of disease causes to prevention and implementation research. The work is supported by extensive
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align with human values and preferences remains a critical challenge, particularly in sensitive domains such as healthcare, education, and governance. Current evaluation methods primarily rely
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. The candidate will contribute to the development of empirically validated methods for identifying and mitigating such effects. The research will involve experimental studies, neurophysiological methods (e.g., eye
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the Computer Science study program. The stipend is open for appointment from August 1st 2025 or soon thereafter. The PhD students will be working on topics within the general areas of formal methods, model checking and