stillingsbetegnelse:
PhD Project in Big Data Modelling with Applications to Airports

jobbeskrivelse:
DTU compute would like to invite applications for a 3-year PhD position starting August 1st 2015. The project is financed by EASI (The Intelligent Transit and Security Trolley – Ultimate Logistic Solutions at Airports) and DTU Compute. Project Description The project deals with data analysis of data from various sources, of high volume, with substantial variance, and with real-time analysis in focus. The aim is to develop statistical techniques to model the data and estimate factors of key interest, as well as explore data to derive new hypotheses of interest. The methodological perspectives will be considered in the framework of a series of applications. In particular, feature extraction and selection methods for extracting relevant information from the massive amounts of data will be a main focus of the thesis. Both supervised and unsupervised models will be explored, and new methods will be developed considering structured information related to correlation structures in the data sources. The correlation structures in data such as videos, images, or various motion tracking devices usually arise due to the underlying continuous processes that are measured. One of the cases will be carried out as part of the EASI project with the aim of developing an intelligent trolley that will make it easier for travellers going through the airport. The trolley will allow scanning of hand luggage directly from the trolley, and therefore make the security pass easier, faster and less stressful for the travellers. In addition the trolley is equipped with a screen guiding the traveller through the airport, using both the screen and knowledge about position. Potentially the trolley will generate a large amount of data, which can be help guiding the traveller, but also have a number of other uses for the airport. Potential factors of interest could be the relation between airport security queuing and changes in shopping behaviour, or luggage scanning indicators combined with unusual individual behaviour. Another available case is a sensitive floor from Elsi Technologies installed at the elderly home Skovhuset. The floor currently aids in guiding the personnel to timely assistance in relation to possible falls as well as other needs. The factors of interest here would be to predict diseases like urinary infections for an early intervention based on the behaviour registered by the sensitive floor (like e.g. registration of frequent toilet visits). The project will include but not be limited to: identification of relevant test cases (possibly including design of experiments), data integration, feature extraction, model development, data mining and machine learning, substantial interdisciplinary collaborations, and scientific dissemination of results. Requirements Candidates must have a master degree in statistical modelling, machine learning, computational science and engineering (CSE), applied mathematics, or engineering, or equivalent academic qualifications. Preference will be given to candidates who can document computational data analysis skills and big data experience, and in addition have a background in statistics. Furthermore, good command of the English language is essential. Approval and Enrolment The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in the ITMAN Graduate School Programme of DTU Compute. For information about the general requirements for enrolment and the general planning of the scholarship studies, please see the DTU PhD Guide. Assessment The assessment of the applicants will be made by: Associate Professor Line H. Clemmensen (supervisor) and Associate Professor Anders B. Dahl (co-supervisor). We offer We offer an interesting and challenging job in an international environment focusing on education, research, public-sector consultancy and innovation, which contribute to enhancing the economy and improving social welfare. We strive for academic excellence, collegial res

Arbejdsgiver Navn: Danmarks Tekniske Universitet

Arbejdsgiver telefonnummer: 45252525

Arbejdsgiver faxnummer: 45881799

Job kort beskrivelse:
Undervisning og forskning på universiteter og højere læreranstalter

land: Danmark

region: Hovedstaden

krævede uddannelse: Ikke angivet

Kilde til jobtilbud: AMS, Offentlige arbejdsformidlinger, Danmark