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machine learning solutions to optimize the component lifecycle directly contributing to a more circular economy. Information In the manufacturing landscape, determining whether a component should be
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: MSc in materials science engineering. Backgrounds in chemistry, physics, computer science or a related area are also welcome. Good expertise or strong interest in numerical modeling, machine learning
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, to either the fixed lines or pooled on-demand vehicles. This requires efficient methods for large scale task assignment and routing leveraging combinatorial optimization and machine learning
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escape. To monitor these mutations and to understand their impact, it is crucial to analyse genomic big data efficiently and accurately. Genomes are studied through genome sequencing, but
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Would you like to work at the intersection of transportation, robotics and machine learning to design mixed fixed-flexible transport networks? Job description The increase of public transport usage
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with disabilities through inclusive Human-Computer Interaction (HCI) and participatory design methods. This PhD project will focus on methods and experiences in co-designing with stakeholders, especially
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diverse team of PhD candidates who will focus on three key areas: Probabilistic and differentiable algorithms for machine learning; Programming language implementation for high performance computing
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theory, discrete optimization and machine learning. In this PhD position you will focus on strain-aware genome assembly, variant calling and strain abundance quantification for viruses, bacteria and yeasts
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PhD candidate will have: Master’s degree (or equivalent) in Human-Computer Interaction, Psychology, or Disability Studies Strong interest in accessibility, assistive technology, human-computer
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trajectories? Passionate about archival research and oral history? Self-motivated and ready to learn new research skills? The Department of History is looking for two PhD candidates to undertake archival and