NLP, graphs and database PhDs adds to NorwAI’s strong base of advanced studies

PERSEUS, a research program collaboration between NTNU, eleven top-level academic partners in eight European countries, and eight industrial partners within sectors of high societal relevance, will partially found four PhD positions at NorwAI, starting from 2022. 

PERSEUS has received funding from the European Union’s Horizon 2020 research and innovation programme, and is the result of a joint effort between departments at the Faculty of Information Technology and Electrical Engineering at NTNU, including members from NorwAI and the Norwegian Open AI Lab. PERSEUS aims at fostering the training of 40 highly skilled doctoral researchers in thematic areas of Big Data and Artificial Intelligence, Digital Twins, Internet of Things, Extended Reality and Information and Cyber Security.

Four PhD students are allocated to NorwAI, of which one is solely PERSEUS funded, will focus in different research areas. Three of the PhDs will be announced in February 2022, in the fourth one a candidate is engaged. 

Natural Language Processing for Personalized Content Summarization

Content summarization uses machine learning to extract the main ideas of individual texts or collections of text. Summarization is often combined with other NLP techniques to provide personalized summaries or build conversational systems that make use of external sources. The PhD student will develop new summarization techniques that are incorporated into generative conversational systems and personalized with respect to users and contexts 

Algorithms for Dynamic Graphs

For many important applications, data is presented as graphs, with dynamic relationships between nodes. Examples include graphs representing the power grid, financial transaction relationships, social networks, and transportation networks. The nodes in the graphs can also have attached dynamic data, for example time series, adding further challenges. The PhD student will develop techniques for efficient processing of such dynamic graphs.

AI for Databases 

The aim of this PhD position is to develop techniques that use AI to improve efficiency of data management systems. Examples of topics in this direction from recent years include learned indexes, machine learning for query optimization, data cleaning, and algorithm selection. The PhD student will work with challenges related to these or other emerging topics within AI for databases.

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Already engaged: Trustworthy Artificial Intelligence

This PhD will contribute to develop principles for creating trustworthy AI applications. Together with partners in the NorwAI SFI the candidate will work on the creation for guidelines for a sustainable and beneficial use of AI, explore privacy-preserving technologies and create explainable, interpretable and transparent prototypes to be tested in industrial settings.

 
More information about PERSEUS: https://www.ntnu.edu/perseus