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<p class="">SnT is a recently formed centre carrying out interdisciplinary research in secure, reliable and trustworthy ICT(Information and Communication Technologies) systems and services, often in collaboration with industrial, governmental or international
partners. SnT is very active in several international research projects funded by the EU 7th framework programme and the European Space Agency. For further information you may check:
<a href="http://www.securityandtrust.lu" class="">www.securityandtrust.lu</a>. The research work will be performed within a young and enthusiastic Big Data working group, established within the larger NetLab research group:
<a href="http://wwwen.uni.lu/snt/research/netlab" class="">http://wwwen.uni.lu/snt/research/netlab</a>.
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The centre is part of the University of Luxembourg and is looking for <br class="">
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PhD candidates in Big Data Analytics for fraud detection (M/F)<br class="">
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<ul class="">
<li class="">Ref: I2R-DIR-PIC-09ESEC </li><li class="">Fixed Term Contract 3 year (CDD), full-time (40 hrs/week) </li><li class="">Number of positions: 2 </li></ul>
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<h5 class="JD-FieldLabel" id="JDLabel-Field2">Your Role</h5>
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<p class="">In the context of a starting collaboration with a partnering company aiming at designing a Big Data like architecture for the detection of fraudulent behavior and anomalies in energy consumption data, the University of Luxembourg is offering two
Ph.D candidate positions at SnT with a focus on the main following activities: <br class="">
1. Anomaly detection approaches for high velocity multidimensional data<br class="">
2. Unsupervised clustering of streaming data<br class="">
3. Distributed (Map-Reduce) like algorithms for massive online anomaly detection <br class="">
4. Concept drift in spatial and temporal feature based data mining<br class="">
5. Feature engineering for classification and clustering<br class="">
<br class="">
The tasks of the Ph.D candidate will consist into performing research analysis as well as designing and evaluating proposed solutions through real implementation in partnership with an industry partner. The research associate will have the opportunity to present
his or her results to the international community by participating to worldwide scientific events.
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For inquiries please contact: Radu STATE (<a href="mailto:radu.state@uni.lu" class="">radu.state@uni.lu</a>)</p>
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<h5 class="JD-FieldLabel" id="JDLabel-Field3">Your Profile</h5>
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<li class=""> A Master’s degree in computer science </li><li class="">Good knowledge in data mining </li><li class="">Good development skills in Java and R, Python </li><li class="">Background in data mining, ensemble learning, clustering </li><li class="">Experience with Big Data frameworks (Hadoop, STORM, Spark/Shark) </li><li class="">A critical mind and openness to technical and scientific challenge </li><li class="">Fluent written and verbal communication skills in English </li><li class="">Commitment, team working and a critical mind </li></ul>
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<h5 class="JD-FieldLabel" id="JDLabel-Field4">We offer</h5>
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<p class="">The University offers 3 year appointment (extension up to 4 years in total is possible).<br class="">
The University offers highly competitive salaries and is an equal opportunity employer.<br class="">
You will work in an exciting international environment and will have the opportunity to participate in the development of a newly created research centre.<br class="">
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</p>
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<h5 class="JD-FieldLabel" id="JDLabel-Field5">Further Information</h5>
<span class="JD-FieldText" id="JDText-Field5">
<p class="">The University offers 3 year appointment (extension up to 4 years in total is possible).<br class="">
The University offers highly competitive salaries and is an equal opportunity employer.<br class="">
You will work in an exciting international environment and will have the opportunity to participate in the development of a newly created research centre.<br class="">
<br class="">
</p>
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<h5 class="JD-FieldLabel" id="JDLabel-Field6">Further Information</h5>
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<p class="">The major topic concerns the analysis of large volumes of energy consumption data. This data in inherent multidimensional with features ranging from location, time, past history, whether and other external data sources. The project will address
both the processing of stored data as well as the analytics of streaming data in order to detect anomalies in historical data, real time correlation with current data and automated clustering using state of the technologies (Hadoop/Shark/Spark/Storm). The
project is hosted in the Netlab research group and will be supported by existing infrastructures and additional expertise in the area of Big Data research. We expect the Ph.D candidate to have a strong motivation in working with an industry leading company
in this area and to be willing in showing leadership, commitment and excellent analytic capabilities.</p>
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<h5 class="JD-FieldLabel" id="JDLabel-Field7">Further Information</h5>
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<p class="">Applications, written in English should be submitted online by 31st March 2015 and should include:</p>
<ul class="">
<li class="">Curriculum Vitae (including your contact address, work experience, publications)
</li><li class="">Cover letter indicating the research area of interest and your motivation
</li><li class="">Copy of your Master’s degree diploma </li><li class="">Copy of your Master thesis (or url to access it) </li></ul>
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