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learning, probability theory, Real and functional analysis, Information-based complexity Appl Deadline: 2026/01/15 11:59PM (posted 2025/12/04, listed until 2026/01/15) Position Description: Position
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have since helped halve global mortality, but this progress is threatened by rising insecticide resistance. We build quantitative, data-driven models to forecast the spread and impact of resistance
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. This research will deepen our understanding of temperature-sensitive reproduction and could ultimately guide new strategies to improve crop resilience in a warming world. For further information and to apply
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sizes and frequencies by: Measuring rock fractures from UAV data using manual and automated mapping approaches (e.g., machine learning, convolutional neural networks). Monitoring physical weathering
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industry and research bodies to drive innovation across all UK manufacturing sectors, from SMEs to large global manufacturers. For details, visit the MTC website . Contact For further information on this PhD
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topic: Capture and model changes in material appearance during exploratory movements. Aim to establish links between material tactile parameters, dynamic changes in the visual information and
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Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg | Magdeburg, Sachsen Anhalt | Germany | about 2 months ago
, analyzing molecular systems, and interpreting chemical data. The project aims at developing a sustainable workflow to design new and 'greener' catalysts and appropriate solvent systems. The role involves
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, copies of relevant certificates and contact information of two scientists as references to: christoph.mayerspam prevention@uni-tuebingen.de The University of Tübingen is an Equal Opportunity Employer with
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of Bradford. This PhD studentship is integrated into work package 5 of the ERC Synergy Subnordica Project, which will combine data from across the entire project into a set of predictive models for comparative
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lack suitable hardware for data collection in the wild, but our ability to process and understand the resulting data suffers from major constraints. Here, advances in AI will be crucial, for instance by