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of hypothermia with important medical implications. To study this, the Ph.D. candidate will use mammalian cells, organoids, and animal models, and employ a range of approaches, including cell culture systems
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getting Bayesian type uncertainty for parameters given data (i.e., a posterior type distribution over the parameter space) without specifying a model nor a prior. Such methods can in principle be applied
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project will be part of the psychology work package which through longitudinal cohort studies with registry linkages and advanced causal modelling techniques will examine the causal relationship between HC
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related algebraic and analytic structures for the analysis and modelling of complex sequential data. Path signatures, originating in stochastic integration and rough path theory, provide expressive
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and analytic structures for the analysis and modelling of complex sequential data. Path signatures, originating in stochastic integration and rough path theory, provide expressive representations
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, invariants, staged rollouts, and rollback mechanisms so that automation remains within sanctioned boundaries. Underpinning both is the need for dependability models that, combined with telemetry-driven
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within sanctioned boundaries. Underpinning both is the need for dependability models that, combined with telemetry-driven learning, can guide self-healing decisions in a way that reduces downtime without
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including multiple and embodied AI agents. Countering the current trends of very large models with hard-to-control outputs, we will focus on balancing data-based approaches with artists’ knowledge and search
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security Semantic modelling of industrial artefacts, knowledge representation and automated reasoning Your supervisor will be Associate Professor Anna Olsen . Your immediate leader will be the Head of
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Model for Integration of Advanced Assistive Technologies (ROBOWELL )”, funded by NordForsk and Novo Nordic Foundation (grant agreement 226198). The project aims to develop a proposal for a Nordic Model