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experience in computational optics, computational microscopy, machine learning. • Open to Fixed Term Contract. Req ID: 33874 Apply now
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to evolutionary time scales. One of the goals of the SCINet Initiative is to develop and apply new technologies, including AI and machine learning (ML), to help solve complex agricultural problems that also depend
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road safety analytics framework. The role involves integrating multi-source transport datasets, developing advanced analytical and machine learning models for risk identification, and supporting
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combination immunotherapies. Development of NK cell and CAR-NK cell therapies. Building on advances in cellular engineering, we develop and optimize NK cell-based immunotherapies, including chimeric antigen
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or machine learning with a particular focus on analysing large-scale behavioural data? Are you interested in developing new methodological approaches capable of extracting behavioural insight from increasingly
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Assurance and Insurance, Quantum Trust, Privacy-preserving Machine Learning, Privacy-preserving Multi-party Computation, Verifiable Computation, Trustworthy Systems, Adversarial Machine Learning, Assessing
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-science and signal-analysis tasks, including processing experimental signals, integrating datasets, developing machine-learning models, and mapping measured fuel properties to SAF performance. For the post
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theoretical statistics, statistical machine learning, high-dimensional inference, empirical process theory, stochastic modeling, optimization, or related areas. • Experience with writing and developing
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are particularly interested in: machine learning for molecular and omics data, including representation learning for biological sequences and structures, and the integration of multiple omics layers machine learning
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, preference will be given to those with strong Python/programming and research skills, and experience in graphs/ontologies, machine learning, optimisation/control, time-series forecasting, BMS/HVAC, PV or ESS