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theoretical evolutionary biology, including optimal control theory, life history modelling, adaptive dynamics, and population genetics. This position is part of the interdisciplinary consortium
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approaches and optimization System dynamics modelling Energy system resilience and risk assessment The research will heavily involve mathematical model development and the use of specialised software
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Description Research Fields Craft science, craft research, consumer studies, social sciences, sociology, economics The Marie Skłodowska Curie Doctoral Network “DyeAnotherWay” is inviting applications for a 36
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, optimize, and expand workflows for spatial omics technologies, from sample preparation through analysis to data generation and interpretation. Integrate spatial methods with other modalities, such as
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) in computer science, mathematics or statistics, with an excellent publication record. Solid research experience in one or more of the following topics is expected: Graph neural networks Optimization
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quantitative predictions testable against empirical data from diverse ecological contexts. We use methods from theoretical evolutionary biology, including optimal control theory, life history modelling, adaptive
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following themes: Traffic modelling and multimodal transport simulation Travel behaviour and choice modelling Network optimization and algorithmic methods Machine learning and data-driven approaches
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optimize project frameworks, drive collaboration across pilot line partners and leading tech companies, and turn innovation into real-world impact. Working at the heart of Europe’s semiconductor ecosystem
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learning models such as Bayesian optimization, neural networks, random forests. A high proficiency in spoken and written English. Excellent communication and interpersonal skills. You are expected to learn
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Investigator (PI) positions. Deadline January 12, 2026. As part of the renowned ELLIS (European Laboratory for Learning and Intelligent Systems) network, we are building a leading center for groundbreaking AI