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description Third-cycle subject: Applied and computational mathematics The Department of Mathematics at KTH is announcing a PhD position in Mathematics with a specialization in AI, focusing on Bayesian inverse
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to AIDS is highly variable among individuals, developing an average of 9-10 years after infection in most adults in the absence of antiretroviral therapy. The overall objective of the PhD project is to
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insights that inform biodiversity management. The project includes: · Apply of deep learning models to annotate bird and bat species from sound recordings. · Develop a Bayesian statistical
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decoupling the key thermoelectric characteristics using a “nanoparticle-in-alloy” design strategy within an inorganic thin-film system. The core objective of the research is to tailor the interface structure
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, a cutting-edge research initiative in forest ecology, biodiversity monitoring, and molecular methods. The project explores how airborne environmental DNA (eDNA) can be used to detect and monitor
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ecology, biodiversity monitoring, and molecular methods. The project explores how airborne environmental DNA (eDNA) can be used to detect and monitor migratory species, invasive species, and pathogens
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systematically integrated into early-stage design and decision-making. The research objective is to support the acceleration towards sustainable and value-creating lifecycle solutions by enabling more informed
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structured communication can support shared decision-making and enhance treatment adherence. Key objectives include: Analyzing and Prevention. Conduct empirical research to: Assess how changes in survival
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inform more targeted prevention strategies. Key objectives include: Analyzing Inequality and Prevention: Conduct empirical research to assess how prevention policies and healthcare innovations affect
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theories from tractable models (probabilistic circuits) and Bayesian statistics to tackle the reliability of machine learning models, touching topics such as uncertainty quantification in large-scale models