School of Computer Science and Electronic EngineeringKTPKnowledge Transfer Partnerships (KTPs) are a unique UK-wide activity that help businesses to improve their competitiveness and productivity by making better use of the knowledge, technology and skills within universities, colleges and research organisations. Further information is available at: www.ktponline.org.ukTHE PROJECTThe University of Essex in partnership with Neotas Limited offers an exciting opportunity to a graduate with the relevant skills and knowledge to utilise a novel combination of natural language processing (NLP) and image analysis to accelerate and automate the collection of Open Source Intelligence (OSINT), i.e., social media postings like Twitter and any other textual/visual user postings on the web, providing end users with advanced insight into individuals, without invading individual privacy. This post is fixed term for 36 months and is predominantly based at Neotas Limited offices in London. Regular visits to the University of Essex for academic exchange and advice are conducted on a weekly basis.DUTIES OF THE POSTThe duties of the post will include:* Develop a novel approach for Open Source Intelligence (OSINT), i.e., social media postings like Twitter and any other textual/visual user postings on the web. * Apply and improve existing methods for text analysis, applied computer vision, and their combination for multi-modal analysis.* Expand the knowledge and technical competence of the [company] by applying a range of the text and vision analysis methods and techniques in operational environment.* Research and identify the latest trends in text and vision analysis, building these into the KTP plan to achieve key project deliverables. * Develop a progressive strategy to enhance the level of meaningful data of Neotas Limited's platform. * Develop new or expand existing algorithms, and develop competency in evaluating which will be most commercially beneficial for Neotas Limited within specific contexts.* Develop commercially relevant solutions to complex data-oriented challenges, and communicate them and the concepts on which they are based in meaningful ways to both company staff and others, where appropriate.* Liaise with commercial partners, suppliers, customers and academic staff.KEY REQUIREMENTSThe post holder must have:* MSc in Computer Science, Data Analytics or Data Science * In-depth knowledge in Text Analytics and applied knowledge in Visual Content Analytics* Good theoretical and applied knowledge in a range of statistical and computational techniques, particularly Natural Language Processing, classification methods and/or machine learning for visual content* Very good knowledge and experience of high level programming languages such as Python* Knowledge and experience of working with machine learning libraries including Deep Learning* Knowledge and experience of working with relational databasesBENEFITSAs a KTP Associate, the post will offer the following benefits:* A personal development budget of GBP 6,000 (exclusive of salary). * Management training and mentoring by an Innovate UK KTP Adviser. * An interesting and challenging role, with exposure to a variety of stakeholders, particularly for accelerating knowledge exchange and transfer from the university to the company.* Full access to university resources to complete the project and encouragement for scientific publication of the project results.* World-leading Academic and Company project supervision, with project support by a dedicated, sector leading KTP Office.LOCATIONNeotas Limited23 Austin FriarsLondonEC2N 2QPAt the University of Essex internationalism is central to who we are and what we do. We are committed to being a cosmopolitan, internationally-oriented university that is welcoming to staff and students from all countries and a university where you can find the world in one place.Please see the further detail link below for a full job description and person specification which outlines the full duties, skills, qualifications and experience needed for this role plus more information relating to the post. We recommend you read this information carefully before making an application. Applications should be made on-line, but if you would like advice or help in making an application, or need information in a different format, please telephone the Resourcing Team (01206 876559).*Further detail: Data Scientist (KTP Associate) jobpack*More information: Working at the University