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Field
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causal inference, integration of heterogeneous data sources, uncertainty quantification Work with a wide range of data types, for example dietary records, biomarkers, omics data, registry data, and sensor
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-after dimension to their research training. The Project The project aims to develop reliable, adaptive, and universal statistical methods a broad range of statistical inference tasks in quantum systems
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chromatographic techniques. Integration and synthesis of previous data with newly collected data on fatty acids, cyanotoxins, and stable isotopes. Application of Bayesian mixing models to investigate consumer diets
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technologies that bridge fundamental research, clinical translation, and real-world healthcare impact. With state-of-the-art infrastructure, strong industrial partnerships, and a proven track record of
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criteria Machine Learning Expertise: A robust foundation in probabilistic modeling, Bayesian inference, deep learning, and/or anomaly detection Modeling & Simulation Experience: Familiarity with Building
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the evolution and adaptation of butterflies flying at high elevations. The goal of the PhD work is to infer signatures of selection in Pierini white butterflies evolving at high elevation in the tropical Andes
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-language-action models, imitation and reinforcement learning, world models, multimodal perception, model compression and edge inference. A key aim is enabling robots to improve beyond initial demonstrations
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beam (FIB) imaging - can be combined with AI to reconstruct nanoscale chip structures and infer functional behaviour from physical layouts. The project addresses the challenge of extracting reliable
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(PEM), and focused ion beam (FIB) imaging - can be combined with AI to reconstruct nanoscale chip structures and infer functional behaviour from physical layouts. The project addresses the challenge
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investigation, one may aim to infer hidden geological or physical structures from measurements such as seismic, electromagnetic, or other indirect observations. Similar challenges also arise in climate and