Are you looking for a PhD position where you can combine insights from machine learning and cognitive science? Are you interested in improving and better understanding artificial intelligence systems for natural language processing? If you are excited about doing this kind of research in an interdisciplinary environment, with a team of smart and friendly colleagues, then you may want to join us at the Institute for Logic, Language and Computation (ILLC).

The Institute for Logic, Language and Computation (ILLC) at the University of Amsterdam and the Department of Philosophy at the University of St Andrews have inaugurated a four year (full-time) Joint Doctoral Programme. The aim of the Programme is to train world-leading researchers in Philosophy, Logic, Language, and Computation.

The PhD candidates admitted to the Joint St Andrews-Amsterdam Programme will be supervised in co-tutelle by academics from both institutions. They will conduct research for at least one year at ILLC and one year at St Andrews. They will be awarded a joint degree and a twofold diploma, with the titles of Doctor for
Amsterdam, and Doctor of Philosophy for St Andrews.

Specific individual student agreements can be designed to suit the needs of each PhD candidate in co-tutelle.

The academic coordinators of the Joint Programme are Luca Incurvati for ILLC, UvA, and Franz Berto for St Andrews. They can be contacted for further information.

Over the last decade, advances in machine learning have taken the computer science community by storm, enabling new applications and pushing the envelope on existing ones. Even on tasks that are traditionally viewed as falling in the domain of logical reasoning (e.g., reading comprehension tasks), deep neural models are now the state-of-the-art. Furthermore, logic and learning are perceived by some as being distinct or even opposing approaches. At the same time, while various algorithmic and hardware limitations that inhibited deep learning solutions in the past have been successfully addressed, other fundamental problems arise, such as problems concerning fairness, explainability, and controllability. In this talk, I will discuss a few problems at the intersection of machine learning and logic, including providing deep models with means to access structured knowledge.

Zoom link: https://uva-live.zoom.us/j/82670894282

Prof. dr. Sonja Smets (Institute for Logic, Language and Computation):
"When agents learn new information they have to be very careful, because the fact of learning information may interfere with the reality that is being learned."
Interviewed by: Dr. J. Ashley Burgoyne (Amsterdam Music Lab).
Zoom link: https://uva-live.zoom.us/j/82520968502