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Field
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model classifiers (PLS-DA, random forest, neural network, etc) towards unraveling materials structure-function relationships, and are familiar with optimization approaches such as genetic search, Bayesian
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, containerization (Docker), Kubernetes API development and web-based analytics tools Systems, Optimization, and AI ML/AI for mobility prediction and optimization Graph algorithms, network science Spatiotemporal
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Bilevel programming (BP) is a powerful mathematical framework for modeling hierarchical decision-making processes involving two players: a leader and a follower. In energy network design, for example
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systems in the face of modern constraints such as optimization under uncertainty, constrained query evaluation, or the design of efficient, explainable, and scalable query engines. The successful applicant
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systems • Healthcare operations, resource allocation, and workflow optimization • Network, graph, and agent-based modeling for care delivery • Health equity, patient access, and system resilience • Multi
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networks (GNNs) to accelerate therapeutic target identification. GenePPS aims to overcome current limitations of perturbation modelling by integrating large-scale single-cell foundation models with
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areas Biomedical applications, social determinants of health or other demographic health areas Spatial microsimulation, spatially weighted regression, combinatorial optimization or Bayesian network
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of the research project “Unreal engines — Understanding language models through resource-optimal analysis: Implicit Bayesian pragmatic reasoning & emergent causal world models”. The project uses
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world-leading fundamental and applied research within communication, networks, control systems, AI, sound, cyber security, and robotics. The department plays an active role in transferring inventions and
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SUSMAT-RC - Postdoc Position in Computer-Aided Design and Discovery of Sustainable Polymer Materials
computational chemistry techniques and data-driven approaches to optimize the properties of novel polymer-based materials. Key duties The successful candidate is expected to: Build and evaluate chemical databases