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on rodent-borne and vector-borne disease systems and their interaction with human mobility and societal connectivity. The project will further develop predictive modelling frameworks to reconstruct and
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system allowing optical holography and patterned photostimulation for causal, ensemble-level manipulation of neural activity. Fully equipped stereotaxic surgery and viral injection pipelines, including AAV
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‑State‑gated, Retro‑Orbital AAVs to Tag & Control Neural Ensembles, an interdisciplinary project jointly led by Stefanos Stagkourakis and William Nyberg and supported by the KI research incubator program
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management. Data from case studies (inspections, monitoring, and experimental tests) are used for model updating, calibration of safety formats, and prediction of future performance and remaining service life
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of computational tools and software for cancer risk prediction. This position offers the chance to engage in cutting‑edge interdisciplinary research at the intersection of ML and cancer research, and to contribute
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will be part of this research ecosystem. Project description A key missing capability in current cancer research is the ability to predict how a particular cancer cell will respond to a perturbation (e.g
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strategies. The research group focuses on exploration of tumor immune microenvironments through spatial omics and imaging, development of computational models for prediction of molecular and clinical features
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and predictive confidence, including sensitivity and identifiability analyses Compare grey-box models against purely mechanistic and purely data-driven approaches Optimize model performance
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: Development of ML/DL methods for multi-omics data analysis. Design and implementation of computational tools and software for cancer risk prediction. This position offers the chance to engage in cutting‑edge
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roughness, AM roughness is characterized by randomness, porosity, and powder adhesion, producing flow behaviors that existing correlations and turbulence models fail to predict. Understanding and modeling