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EU MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of
between process parameters and material properties will be developed and subsequently exposed to Bayesian optimization to find the optimal set of parameters that improve process performance and material
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. Additional qualifications: It is advantageous to have experience in one or more of the following areas: Machine Learning & Bayesian optimization (Python, Supervised learning, Multi-objective optimization
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to have experience in one or more of the following areas: Machine Learning & Bayesian optimization (Python, Supervised learning, Multi-objective optimization) Additive manufacturing of metals Corrosion
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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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and regulatory context. Objectives Develop an agent-based modelling and stakeholder analysis toolkit to capture the perspectives, needs, and regulatory constraints of main stakeholders. Design modular
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research and soft robotics development. PhD project The PhD project will focus on the technical aspects of simulating the physics of the Drosophila larva body. The primary objectives include: Developing a
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risk development. These projections will enable the identification of sustainable adaptation strategies and support policy development. Objectives Develop an Agent Based Model (ABM) that describes flood