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-funded project Print4Life, a Marie Sklodowska-Curie (MSCA) doctoral network led by Prof. Cecilia Persson, Uppsala University. Print4Life – Advanced Research Training for Additive Manufacturing
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health. You will develop and apply cutting-edge machine-learning techniques to identify the most informative indicators of ecosystem change and use them to build dynamic Bayesian network (DBN) ecosystem
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. There will also be common meetings with the other 14 PhD students in the doctoral network, including 3 training schools. As a participant of the project, the PhD student will become part of a team at DTU
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Denmark and Politecnico Di Torino, Italy. There will also be common meetings with the other 14 PhD students in the doctoral network, including 3 training schools. As a participant of the project, the PhD
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modelling approach, and dynamic Bayesian Networks would be advantageous. Willingness to conduct research in a multi-national project team. Funding requirements: You cannot have resided in The Netherlands in
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with process safety and security concepts, accident modelling approach, and dynamic Bayesian Networks would be advantageous. Willingness to conduct research in a multi-national project team. Funding
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also be part of the MBIC Graduate School, which provides additional training and networking opportunities. Predictive processing is increasingly recognized as a key computational principle of brain
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, particularly NaTech (Natural Hazard Triggering Technological) events. REUNATECH is a Horizon Europe Marie Skłodowska-Curie Doctoral Network that aims to educate and train the new generation of Doctoral
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with process safety and security concepts, accident modelling approach, and dynamic Bayesian Networks would be advantageous. Willingness to conduct research in a multi-national project team. Fluent in
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processes related to carbon cycling in the soil-plant system Experience with Bayesian inference and machine learning is an asset Ability to work independently and cooperatively as part of an interdisciplinary