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into the vegetation. Within this European project, the University of Trento (Department of Information Engineering and Computer Science) leads the research activities related to electromagnetic modeling and digital
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Postdocs in Generative Machine Learning for Biomedical Data. The postholders will focus on developing and applying state-of-the-art generative models (such as VAEs, GANs, and transformer-based architectures
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Model. Adv. Sci. 2025, 2500400. https://doi.org/10.1002/advs.202500400 Research Area Applications are invited from outstanding candidates with expertise in molecular biology, biotechnology, and/or
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, communication algorithms) Parallel programming models and runtimes for emerging architectures (e.g., processing-in-memory, SRAM-centric) Performance modelling & optimisation of ML algorithms on unconventional
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including D-branes, Black Holes, Gauge/string theory duality, Phenomenological String theory/M-theory; Particle Phenomenology including Physics beyond the Standard Model, Dark Matter, Axions, Higgs and
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, spectral matching against databases (e.g., Metlin, KNAPSAcK), and statistical modeling for biomarker discovery. Integration and Interpretation: Correlate metabolomics data with biological and geographical
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knowledge in the field of ecosystem dynamics and computational oceanography, through the development or application of theoretical, numerical, or modelling approaches for the study of physical and