Project FORGET – Forgetting what Needs to be Forgotten (PTDC/CCI-INF/32219/2017)

Being able to selectively forget information from data and knowledge bases is fundamental to properly deal with legal and privacy issues, for instance to implement court decisions ordering the elimination of illegally acquired or maintained information, or to comply with the right to be forgotten, recently enacted in the EU General Data Protection Regulation. However, forgetting is not as easy as deleting the item to be forgotten, since additional changes may be required to keep the intensional meaning of the remaining data and knowledge, and to guarantee that the forgotten information cannot be recovered from the stored results of previous computations that used it. The FORGET project will develop a principled solution, composed of theory, methods and tools, to effectively and efficiently forget selected information from data and knowledge bases, while preserving what should not be forgotten.

Project RIVER – Reasoning with Knowledge and Data Streams (PTDC/CCI-INF/30952/2017)

Recent developments originally triggered by initiatives such as the Semantic Web, Linked Open Data, and the Web of Things, resulted in the wide and increasing availability of machine-processable data and knowledge in the form of data streams and knowledge bases, which is preparing the ground for a new class of dynamic, rich, knowledge-intensive applications. Examples can be found in domains such as the Smart Grid, assisted living and alarm handling in telecommunications. These require automated reasoning with the integration of several heterogeneous knowledge bases (KB) together with several heterogeneous data/event streams to support automation and problem-solving, enforce traceable and correct decisions, and facilitate the internalization of relevant dynamic data and knowledge and the project will provide the necessary theory and tools to deal with such heterogeneous KB and data/event streams in an integrated way and apply them to two practical use-cases.

PostDoc positions

For PostDoc positions, candidates should hold a PhD. or equivalent degree. Excellent candidates in a final phase of their PhD. studies can also be considered. Suitable disciplines include Computer Science, Artificial Intelligence, Mathematics, Machine Learning and other related areas. A strong publication record is considered a plus. Candidates are expected to be fluent in spoken and written English. PostDocs can, optionally, supervise MSc and PhD projects.

The positions are available immediately but the start time can be negotiated. The positions are fixed-term and filled initially for 1 year with an option for extension of 1-2 years.

Applicants should express their interest by sending the following documents by email according to the instructions below:

– a cover letter briefly describing your background and interests;

– a Curriculum Vitae (with contact details);

– names and contact information (email) of at least two references;

– a link to electronic copy of Ph.D. Thesis (if available);

– links to electronic copies of 1-2 most relevant publications.                   

PhD Student positions

For PhD Student positions, candidates should hold a MSc. or equivalent degree in a suitable area (e.g. Computer Science, Artificial Intelligence, Mathematics, Machine Learning) or be a MSc Student in a final phase of studies. Candidates are expected to have good programming and mathematical skills, and be proficient in spoken and written English. 

Excellent candidates in a final phase of their Ph.D. studies can also be considered. Suitable disciplines include Computer Science, Artificial Intelligence, Mathematics, Machine Learning and other related areas. A strong publication record is considered a plus. Candidates are expected to be fluent in spoken and written English. 

The positions are available immediately but the start time can be negotiated. The positions are fixed-term and filled initially for 1 year with an option for renewal.

Applicants should express their interest by sending the following documents by email according to the instructions below:

– a motivation letter;

– a Curriculum Vitae (with contact details);

– names and contact information (email) of at least two references;

– transcript of records (courses and grades)

– a link to electronic copy of MSc Thesis (if available);

– a list of publications (if available)                   

Contact Information:

Send the documents by email both to Joao Leite <jleite@fct.unl.pt> and Matthias Knorr <mkn@fct.unl.pt> with subject "PostDoc/PhD Student call KBS 1/2018".

Deadline: November 14th, 2018.