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(FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission
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, Mexico City 04510, Mexico [map ] Subject Area: Probability Appl Deadline: 2025/05/30 11:59PM (posted 2025/04/11, listed until 2025/05/30) Position Description: Apply Position Description The Instituto de
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for healthcare. A2 Project or subject specific skills; e.g. experience of data collection, the use of AI/ML tools for processing collected data and understanding of hardware technologies to configure systems and
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systems of differential equations. The resulting models will be analysed with analytical tools from applied mathematics and numerical studies in the Julia programming language. The successful candidate
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, classical ecological theories and methods to mathematically model species interactions networks and communities across spatial scales. As part of the project, the student will extend these methods and make
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Technology, Campus Norrköping. Your work assignments This position is motivated by the need for reliable visualization and data analysis methods that support understanding of the increasing amount
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mathematics is essential. Prior experience with simulation tools or microstructural modelling is desirable. To apply, please contact the supervisor, Prof Andrey Jivkov - andrey.jivkov@manchester.ac.uk . Please
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to produce resilient and high-performing models. · PhD in Computer Science, Machine Learning, Mathematics, Physics, Statistics, or a related field Strong track record of applying ML in academic or industry
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food trade model is used to study the impacts of AMOC collapse on global food security. Your qualities We are looking for inspiring and driven candidates who have: a MSc in physics, applied mathematics
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psychology A successfully completed scientific university degree in psychology Accurate working and strong team spirit Confident handling of large, longitudinal data sets Competent use of statistics and data