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Field
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methods requires large investments, with uncertain returns; and there is a lack of strong leadership to drive change in this polarised field. Ombion CPBT is a national centre with a unique infrastructure at
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intelligence (AI) to optimize large dataset analysis, improving decision-making processes for awarding grants to firms and scientists. Key research areas include: Enhancing Selection Decisions: How can we make
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methods for causal inference in observational data, is strongly preferred. Using various existing large datasets with rich information for knowledge synthetisation and triangulation over the course of the
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effective delivery of expertise, equipment, and medical resources in response to complex and large-scale emergencies across the United Kingdom. In its initial phase, the research will examine past and
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will examine and develop methods that go beyond the Markovian paradigm. It will consider a range of time series data, focusing on those that show challenging properties of uncertainty, irregularity and
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Human Behaviour in projects targeting social good. Research at N/LAB focuses on the development and application of innovative computational methods using Big Data, Behavioural Science and Machine Learning
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collaborations. Practical experience with waste materials, and experience in laboratory work related to microplastics and/or chemical risk assessment is a large plus. A proactive and independent work style. A
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existing data analytics tools will help deploy these technologies in the industry context without the need for big datasets. Predictive Maintenance (PdM) is one of the maintenance strategies that has
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) out to 2050. Tasks include compiling big-data inputs, developing CNOSSOS-EU compliant simulations, validating predictions with field/lab measurements and mapping future hot-spots. Ideal profile: honours
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in expressing and purifying large multi-subunit protein complexes and analysing them through in vitro methods. Extensive experience in structural biology techniques, especially with cryo-EM