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Field
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will be hosted by the School of Mathematical Sciences in UCC. This role is part of a national Centre, Rinn Artificial Intelligence – Research & Innovation in Data Science and AI, a multi-institutional
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is required. Preferred: Molecular modeling expertise would be beneficial. Experience with conducting structure-activity relationship studies is preferred. Experience with high-throughput synthesis and
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, applied mathematics, computational science, biophysics, biomedical engineering, or a closely related field. Strong background in nonlinear continuum mechanics, tensor algebra, and finite element modeling
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Qualifications: Doctoral degree. Applicants background may include studies in: Computational Science, Computer Science, Applied Mathematics, Engineering and Physics. Additional Qualifications: Expertise (or desire
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In collaboration with Utrecht University, you will quantify fire dynamics and its impacts on vegetation and climate at regional scales, combining global vegetation models with state-of-the-art
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Job Description Required Qualifications: (as evidenced by an attached resume) PhD, MD, or MD/PhD (or foreign equivalent). At least one academic degree in the field of Mathematics, Physics, Biomedical
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. The candidate will apply a suite of statistical and physical models for integrating observations of different accuracies, improving predictions of future hazards. The work will further include research, writing
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(OVG) as part of the Correlates of Immunity – Artificial Intelligence (CoI-AI) Programme, a pioneering initiative that integrates controlled human infection models, advanced immunology, and AI-driven
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should hold a PhD (or be close to completion) in a relevant analytical and quantitative discipline, such as civil or transport engineering, transport modelling, mathematics, statistics, data science
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Post-Doctoral Associate in the Center for Interdisciplinary Data Science and Artificial Intelligence
of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large language models Statistical learning theory and complexity analysis Automated theorem proving and formal methods