PhD Position in Causality for Domain Adaptation and Optimization

Updated: 4 months ago
Deadline: 31 Jan 2022

Faculty of Science

A prominent research topic at the UvA is Artificial Intelligence. The UvA is part of the AI Technology for People initiative, where it teams up with several other key players within the Amsterdam region. Together they will invest 1 billion euros in the development of responsible AI technologies over the next ten years by setting up research programmes, attracting top scientists and educating students with state-of-the-art knowledge of AI.

The UvA was selected by the European Laboratory for Learning and Intelligent Systems  (ELLIS) as an Excellence Centre for AI to help keep in Europe talent in machine learning and related AI research fields. The UvA is also involved in various labs of the Innovation Centre for AI  (ICAI), which promotes public-private partnerships in the general area of AI.

One of these ICAI labs is the newly established Mercury Machine Learning Lab . In this lab, researchers from the University of Amsterdam (UvA) and Delft University of Technology (TU Delft) will be working together with  on various improved recommendation systems. The collaboration provides the unique opportunity to test AI techniques in the real world, allowing new machine learning methods to be safely developed for wide application, for example in mobility, energy or healthcare.

The UvA researchers participating in the MMLL have different areas of expertise and are affiliated with various research institutes of the Faculty of Science. Prof. dr. De Rijke  specializes in information retrieval and is affiliated with the Informatics Institute . Prof dr. Mooij  specializes in causality and is affiliated with the Korteweg-De Vries Institute for Mathematics . Dr Titov  and Dr Aziz  both specialize in NLP and are affiliated with the Institute for Logic, Language and Computation .

The researchers affiliated with the TU Delft  that are involved in the MMLL are Dr Spaan  and Dr Oliehoek , who both specialize  in reinforcement learning. In addition to the existing researchers, the Mercury Machine Learning Lab will comprise six PhD candidates and two postdocs who will work on six different projects related to bias and generalisation problems over the course of the next five years. They will spend two days a week in the office of in Amsterdam to do research and actively participate in related streams of experimentation to test their hypotheses. More information about the Mercury Machine Learning Lab and the related projects can be found on the MMLL website .

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