Demokritos and Qualco: Fellowship Programme Announcement
While it is a cliché to observe that data is the gold of the 21st century, few have considered the role of processing in this metaphor: raw data must be processed to become precious. At the scale of most businesses, the volume of data is too great for humans to handle, so we must turn to data science.
Demokritos NCSR and Qualco join forces to develop a highly selective program to open up new opportunities for talented researchers to pursue their ideas and lead an ambitious scientific project. Through this ambitious and dynamic fellowship program it is defined the role of Artificial Intelligence (AI) and Big Data Analytics in the Fintech Industry.
The program’s achievement is to facilitate the rapid incorporation of research results in products and services with huge financial and social impact. The program has as ultimate goal to help students explore the FinTech landscape and ecosystem and grappling with the potential direction of future change.
Qualco endorsed a 5-year partnership with Demokritos NCSR, to support research and development (R&D) projects, which include Ph.D. and Post-Doctoral research, scientific projects, innovative workshops and competitions.
The program includes 2 Domains:
1. Utilizing unstructured, semi-structured and fully structured data to empower fintech analysis. A wealth of information exploitable for fintech analysis is available in various levels of structure: from databases and data warehouses, to XML and HTML documents to free text, this wealth can be challenging to capture, classify and in the end - utilize effectively. This domain undertakes research on methods that identify, extract and organize rich information from different sources with varying structure in their data, rendering them useful in fintech processes. Suggested topics for Post Doc/Ph.D. Research:
Text analytics in blended semi-structured and structured (big) data for (dynamic) predictive modeling in the financial domain.
Unstructured natural language processing (NLP) and text mining as significant features for the identification of opportunities and risks in the financial domain.
2. Tapping into natural language as an information source for fintech. In direct and indirect expression, humans produce a multitude of signals usable in processes such as customer support, sales, human resources, negotiation and other settings. This domain undertakes research on methods that employ natural language processing (NLP) and related disciplines to harness the knowledge transferred through explicit and implicit language signals, to support fintech products and services including decision support and real-time analytics. Suggested topics for Post Doc/Ph.D. Research:
Conversation (multi-modal) sentiment analysis
Speech summarization in Fintech context
Argument mining from textual conversations
Utilizing NLP for intelligent, real-time, interactive analytics and pattern identification on Fintech data
Are you interested?
You can read more about what we are looking for, requirements and what your application must include.