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/careers ). YOUR PROFILE PhD in biology, mathematics, or a related field Strong background in mathematical or computational modelling Ability to develop and pursue independent research questions Interest in
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FieldPhysicsYears of Research ExperienceNone Additional Information Eligibility criteria - A PhD in mathematics/statistics/AI applied to ecological issues. - A strong publication record. - Proficiency in R and Python
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development of new computational and mathematical models to quantify and predict infectious disease risk, particularly for identifying high risk individuals and groups. The PDRA will translate conceptual
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Hopkins University (USA), and Google Deepmind (London).* About the role The PDRA will lead the development of new computational and mathematical models to quantify and predict infectious disease risk
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and experience: Essential criteria PhD in applied mathematics, statistics, engineering, computational biology, econometrics, or a related discipline. Experience in developing complex models using real
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others, pseudospectra theory, and empirical data from DRAGNet and global demographic databases (COMPADRE, COMADRE, PADRINO). The project combines mathematical modelling, simulation, and empirical synthesis
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for mapping processes. Moreover, the successful candidate will support other activities in WP2 by integrating the models into AI-based perception systems, contributing to creating multi-modal ecological maps
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fertilization). The work aims to identify the key ecological factors influencing the adoption of crop rotation in agricultural systems. Key responsibilities: Model crop rotations in space and time: development
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of organic soils, and process modelling. The position is available immediately, with a start date as soon as possible. Your qualities a PhD degree in a relevant discipline, such as environmental sciences
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candidate with a PhD in ecology, ecotoxicology, or environmental modeling, and strong analytical and programming skills (e.g., R or Python). Experience with biodiversity metrics, ecosystem service modeling