Research Associate; Postdoc in Blockchain Analytics and Data Engineering

Research Associate (Postdoc) in Blockchain Analytics and Data Engineering

The University of Luxembourg is an international research university with a distinctly multilingual and interdisciplinary character.

The Interdisciplinary Centre for Security, Reliability and Trust ( SnT ) at the University of Luxembourg is a leading international research and innovation centre in secure, reliable and trustworthy ICT systems and services.
We play an instrumental role in Europe by fueling innovation through research partnerships with industry, boosting R&D investments leading to economic growth, and attracting highly qualified talent.

Welook for researchers from diverse academic backgrounds to contribute to our projects in areas such as:
Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and ICT Services & Applications.

Successful candidates will join the young, vibrant, and interdisciplinary FINATRAX Research Group, which builds bridges between business research and information systems engineering. The group conducts research on the application and the impact of digital technologies on organisations in the private and public sectors. Our team consists of international researchers with backgrounds in computer science, engineering, information systems, economics, management, law, and other fields, united in pursuit of sustainable technologies that positively impact society.

For more information, please visit our website:(Use the "Apply for this Job" box below)./

In the context of Prof. Fridgen’s Pay Pal-FNR PEARL Research Grant and the Future Fin Tech  National Centre of Excellence in Research and Innovation, the successful candidate will work at the intersection of data science, blockchain technology, and financial crime prevention, performing the following tasks:

• Conduct and supervise cutting-edge interdisciplinary research building on the analysis of large-scale blockchain data. This will include, but is not limited to:
  • Designing, implementing, and maintaining scalable pipelines that ingest raw on-chain data (blocks, transactions, smart-contract events) from public blockchains into research-grade databases
  • Developing statistical, graph, and/or machine learning models to study transaction networks, illicit transaction patterns, and DeFi protocol operations
  • Creating and evaluating tools, documentation, and open datasets
• Collaborate with researchers in law, finance and economics on topics such as governance, regulatory compliance (e.g., MiCA Regulation, AML/CTF), sustainability, and digital identity
• Disseminate results by publishing in highly-ranked outlets in information systems and computer science
• Communicate and work with governmental stakeholders, analytics vendors, and financial institutions to gather requirements, obtain datasets, and validate results
• Manage research projects and deliverables, as well as prepare research proposals to attract public and private funding
• Mentor and supervise PhD students and student assistants working on related topics
• PhD in Information Systems, Computer/Data Science, Software Engineering, Applied Mathematics, or a related field
• Experience in publishing high-quality research, as demonstrated research under review or published in well-ranked conferences and journals
• Research experience with blockchain and Web-3 data (e.g., Ethereum, Solana, Bitcoin, DeFi protocols)
• Familiarity with smart contract interaction (e.g., web
  3.py/ethers.js, Solidity/Vyper, sub-graph indexing), and local development/testing frameworks such as Hardhat, Truffle, and Ganache
• Basic knowledge of blockchain APIs or analytics platforms (e.g., Dune, Nansen, Graph, Arkham)
• Interest in blockchain-related research topics such as token-economic design and incentive mechanisms, DeFi protocol mechanics, on-chain privacy techniques (e.g., mixers, zero-knowledge proofs), and the relevant regulatory landscape (e.g., AML/CFT, MiCA)
• Willingness to work in a highly interdisciplinary context and develop a set of interdisciplinary methods (i.e., dealing with both qualitative and quantitative data)
• Interest in engaging with stakeholders…