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Post-Doctoral Associate in the Center for Interdisciplinary Data Science and Artificial Intelligence
Statistical learning theory and complexity analysis Automated theorem proving and formal methods Random matrix theory and its applications in modern AI systems Requirements: PhD in Mathematics, Computer Science
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and algorithmic perspectives on large language models Statistical learning theory and complexity analysis Automated theorem proving and formal methods Random matrix theory and its applications in modern
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-based information systems using both quantitative and qualitative approaches. Investigating and applying AI as a research method in IS e.g., computationally intensive theory construction Prepare research
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requirements for the Ph.D. but whose degree has not yet been formally conferred may be eligible to begin employment provided they submit an official letter from the Registrar or Graduate School of the degree
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at the University of Luxembourg brings together researchers from a range of disciplines using qualitative, quantitative and mixed methods approaches, often working across disciplinary boundaries and in close
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developing generic tools that take a declarative problem description and automatically compute an optimal solution to it. Often, users specify their problem in a high-level, human-understandable formal
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EXPERIENCE in: Scientific/Academic writing Research methodology (Quant or Mixed Methods) Experience with statistical software (e.g., R, Mplus, SPSS, etc.) Credentials must be obtained prior to the start date
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to evaluate the effects of adaptive dialogue strategies on engagement, openness, curiosity, empathy, and reflection; Contribute to reusable experimental infrastructure, datasets, evaluation methods, and
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. Hands-on experience of LC-MS and tandem MS for untargeted and/or targeted analysis. Experience developing or optimising sample-preparation methods for biological matrices. Desirable Criteria: Experience
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excellent communication skills and organization. The laboratory uses immunological methods, molecular biology, cellular biochemistry, redox biology, murine models, imaging, and flow cytometry to discover and