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Roles we're recruiting for in 2016 are listed below.


The post-holder will undertake the development and the day-to-day management of the Legal Innovation Centre, in the role of Director, in liaison with and under the shared line management of Executive Directors Dr Kevin Curran, School of Computer Science and Dr Eugene McNamee, School of Law.  Given that the Centre is a new venture creating a bridge between Law and Computer Science to the end of fostering and creating legal service provision innovation and advancing educational provision in Legal Technology, the day to day management will be initially largely focused on developmental activity in research and course provision.  In research the principle tasks will be: in liaison with Executive-Directors, seeking external collaborative partners for projects on the borders of law and technology, supervising and facilitating the realisation of such projects through internal coordination with existing staff in both Schools (and other university staff as appropriate), preparing grant applications to generate funding for internally generated research projects, liaising with Office of Innovation to develop marketable ideas and to ensure full copyright protections, legal compliance etc.  In course provision, to develop and teach the existing LLM module in Legal Technology, to develop an undergraduate module in Legal Technology (industry collaboration in the running of these courses would be encouraged) to develop a CPD professional short course in Legal Technology to be offered externally, to develop as appropriate an outline plan for a complete LLM in Legal Technology.

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Research Associate

Legal Language Identification Intelligence

The post holder will develop software to rapidly and accurately face check legal documents using computational intelligent language techniques. S/He will be required then to formally report progress both written and verbally and to provide high quality journal paper outputs.The aim is to extract and verify each fact in legal texts and to create a broad set of enabling tools to assist in the verification of relevant facts. Knowledge acquisition rules, based on the linguistic treatment of specific aspects of legal documents will be the key to improving the results in this task. This post will involve the creation of language models for addressing information extraction from texts in the legal domain combined with external publically accessible document silos in order to verify statements. Automatic fact checking of legal documents allows for improvements in legal information retrieval system effectiveness. This will be achieved using a number of software tools connected through Application Programmer Interfaces (APIs) and applied to existing legal documents.

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