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Northeastern University London Fully Funded PhD Scholarship in Computer Science Reliable Quantum Statistics Northeastern University London > Computing, Mathematics, Engineering & Natural Sciences
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: Certified unlearning with formal guarantees — developing methods with provable erasure bounds, connecting to differential privacy and statistical divergence frameworks Robustness to adversarial relearning
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Statistical methods are leveraged in many scientific applications to: specify a data collection practice (experimental design), draw conclusions from sparse and noisy data (inference), and assess
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develop AI tools for the interrogation of subcellular proteomics data. We are interested to hear from candidates with experience in probabilistic or statistical modelling of complex biological data, such as
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the best outcome. Precision medicine methods leverage individual-level characteristics to help optimise treatment choices for individuals. This project will leverage recent advances in Bayesian statistical
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statistical approaches to characterise disease trajectories, develop risk prediction models, and identify factors associated with differential treatment outcomes. The findings will improve understanding of long
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-tube system. All datasets will be integrated into a comprehensive data analysis workflow, using statistical and forward modelling methods to calibrate and validate numerical models. This combined
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idea in more detail using novel genetic epidemiological techniques in large global biobanks. The student will train in 3 world leading centres and will gain skills in immunology, statistics and genetic
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that HbA1c can sometimes lead to incorrect management of diabetes. To address this problem, the project will use statistical genetics to untangle these distinct biological pathways. By separating the genetic
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PhD Studentship: Designing Human-AI Teams for Meaningful Human Control of 'Machine-Speed' Operations
necessary. Previous experience with experiments involving human participants (particularly in decision making and / or teams), and statistical analysis of data is essential. Familiarity with agentic AI