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to train neural networks to extract and interpret these complex relationships [10]. To address the challenges of quantitatively analysing the physico-chemical effects underlying the hydrogen/air combustion
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, physical chemistry, and biology, enabling the center to hold a prominent international position in the flagship field of glycoscience—from complex carbohydrates (sugars, oligo- and polysaccharides
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finite-difference resolvent solver incorporating stabilising filters as well as a domain-decomposition strategy suitable for complex geometries, - Use efficient time-integration methods to compute
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-associated alterations in complex neurological and cancer disorders. For further information about this role, please contact Enrico Glaab: Your profile The candidate will have a MSc or equivalent degree in
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projects enabling secure, interoperable, and scalable AI-driven use of clinical data for complex diseases such as Alzheimer's and Parkinson's. You will work within a multidisciplinary environment alongside
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embedded in the Doctoral Programme in Complex Systems Science at the University of Luxembourg. The modelling approaches developed in this project share conceptual similarities with adaptive network and
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will be embedded in the Computational Mechanics (Legato ) group and enrolled in the Doctoral Programme in Complex Systems Science. Depending on background and interests, the PhD may include: Development
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into an early‑warning monitoring framework. The successful candidate will pursue three core research directions: Developing a foundation model capable of identifying ECs directly from complex LC‑HRMS
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, implementing, and solving complex optimization problems (e.g. linear, nonlinear, mixed-integer, or multi-objective optimization) Experience in energy management of renewable energy sources coupled with energy