PhD candidate in Big Data Analytics for Insights into Bitcoin Usage

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 (www.securityandtrust.lu). The research work will be performed within a young and enthusiastic Big Data working group research group, SEDAN (Service and Data Management in Distributed Systems) http://wwwen.uni.lu/snt/research/sedan. We are looking for a PhD candidate strongly motivated in working with an industry leading company in this area and to be willing in showing leadership, commitment and excellent analytic capabilities.

  • PhD candidate in Big Data Analytics for Insights into Bitcoin Usage (M/F)
  • Ref: R-STR-5012-00-B
  • Fixed Term Contract up to 3 years, pending satisfaction of progress milestones (CDD), full-time (40 hrs/week)
  • Number of positions: 2

Your Role

The research work is done in the context of a starting collaboration with a partnering company ScoreChain (link to website), in the area of real time analytics and query of Blockchain and Bitcoin transactions. The major topics concern the development of Big Data Architectures allowing the storage, streaming analytics and advanced query of the Blockchain. Moreover, compatibility with existing blockchains (Ethereum) is required. The research work will address also the development of heuristic algorithms for large graph traversal and processing in order to perform advanced AML (Anti Money Laundering) and digital forensic investigations. For this task, the project will develop behavioural profiling approaches for mining pools, wallets and specific network level information sources. Because of project driven agile development, additional analytics for Blockchain specific tasks will be required.
The tasks of the PhD candidate will consist into performing research analysis as well as designing and evaluating proposed solutions through real implementation in partnership with an industry partner. A strong commitment for collaboration with an industrial partner is required. The researcher will have the opportunity to present his or her results to the international community by participating to worldwide scientific events. More specifically, the work will address the following issues:

1. State of the art research in existing data mining approaches for the Blockchain networks
2. Practical assessment of open source and commercially (if needed) tools required for the concrete project (BigChainDB, Cassandra, Spark)
3. Exploratory data analysis on the dataset in order to identify the relationships among the different features (PCA, factor analysis, correlations, etc).
4. Identification of relevant large-scale graph based analytics algorithms.
5. Scalable scoring engine based for wallets and transactions
6. Realistic field trial and model updating to match with real-world requirements and experience.

For inquiries please contact: Radu STATE (radu.state@uni.lu)

Your Profile

  • A master’s degree in computer science (at least 120 ECTS or equivalent)
  • Good knowledge in data mining
  • Good development skills in Java, Node.js, Python
  • Background in data mining, ensemble learning, clustering
  • Experience with Big Data frameworks (Hadoop, Spark/Shark)
  • A critical mind and openness to technical and scientific challenges
  • Fluent written and verbal communication skills in English
  • Commitment, team working and a critical mind

We offer

The University offers a Ph.D. study program with a Fixed Term Contract up to 3 years (extension up to 4 years in total is possible), pending satisfaction of progress milestones (CDD), on full time basis (40hrs/week). The University offers highly competitive salaries and is an equal opportunity employer.
You will work in an exciting international environment and will have the opportunity to participate in the development of a newly created research centre.

Further Information

Applications, written in English should be submitted online and should include:

  • Curriculum Vitae (including your contact address, work experience, publications)
  • Cover letter indicating the research area of interest and your motivation
  • Copy of your Master’s degree diploma
  • Copy of your Master thesis (or url to access it)

Deadline for applications: 30/10/2016

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