剑桥大学PhD position in Deriving causal factors from a large scale decision corpus申请条件要求-申请方
主办方
剑桥大学
PhD直招介绍
About the Project
AI_CDT_DecisionMaking
Details
There is a huge amount of published literature describing tens of millions of evidence trials for various aspects of human endeavor, ranging from medicine to conservation to socioeconomic development. With modern machine learning, we now have the opportunity to analyse this literate at scale, and identify causal factors across multiple trials under seemingly diverse circumstances. For example, in the case of conservation evidence, we can identify experiments about one particular intervention ("reducing pesticides to prevent bee colony collapse") and measurements ("pesticide levels"), but identify other possible causal factors around ("microplastics from a nearby recycling facility") causing the pollutant. By running LLM-structured searches across the full body of literature which contains many trial results, we can now identify many more potential causal factors to help with further hypothesis generation and testing. Our initial focus is on conservation evidence (conservationevidence.com), but we plan to expand into other areas such as education effectiveness and socioeconomic interventions. A key goal is to construct a usable interface to these searches such that non-expert policymakers can access this capability without programming or machine learning experience. Data availability. This sort of analysis is possible due to a new corpus of literature we have assembled in Cambridge, in collaboration with the Office of Scholarly Communication, to download the full texts and metadata for millions of academic papers (including non-open access ones). We will conduct the causal analysis across this dataset, and also include further "grey literature" and eventually widen the document corpus to non-scientific literature (such as planning and policy documents).
The University actively supports equality, diversity and inclusion and encourages applications from all sections of society. We place major emphasis on the importance of team work and an enjoyable work environment as a foundation for performing internationally leading research. This will allow the student to acquire cutting edge research methodologies in a supportive environment, where they can focus on making the best possible scientific progress.
剑桥大学 PhD position in Deriving causal factors from a large scale decision corpus项目有没有奖学金，是不是全奖Phd招生，下面我们一起看一下【大学名称】Phd的奖学金资助情况
项目资助情况
This is a fully funded AI UKRI CDT 4 year program; Home tuition fees will be provided, along with a tax-free stipend (subject to individual circumstances), set at the UKRI rate (e.g. £19,237 for 2024/25) . The start date is September 2025.
Project based in University of Cambridge.
联系人
邮箱：aidecisionscdt@manchester.ac.uk
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