Please note, this is a continuous program until 2022, with student intakes in September every year (and potentially in March). Hence, please feel free to apply at any time, or if the application page is currently closed, wait for a few weeks until applications are open again. If you have administration questions (e.g. about deadlines) contact the CRTs directly.

Science Foundation Ireland (SFI) agreed to fund several Centres for Research Training (CRT), and I will be involved in two of them, focusing on, among others, artificial intelligence, machine learning, automated machine learning (AutoML), meta-learning, recommender systems, and virtual/augmented reality:

  1. SFI Centre for Research Training in Digitally-Enhanced Reality (D-REAL)
  2. SFI Centre for Research Training in Artificial Intelligence (CRT-AI)

D-REAL and CRT-AI seek to hire more than 240 PhD students in the next four years, i.e. around 60 per year (30 in each CRT).

I am offering two projects in the CRTs:

Deep Meta-Learning for Automated Algorithm-Selection in Information Retrieval
The Automated Machine Learning (AutoML) community has made great advances in automating the algorithm selection and configuration process in machine learning. However, the “algorithm-selection problem” exists in almost every discipline, be it natural language processing, information retrieval, or recommender systems. Our goal is to improve algorithm selection in information retrieval and related disciplines (e.g. NLP) through AutoML techniques such as meta-learning. The idea behind meta-learning is to use machine learning / deep learning to learn from large amounts of historic data how algorithms will perform in certain scenarios. Your work might be integrated into our real-world recommender-system as-a-service that delivers millions of recommendations to our partners. This PhD project will additionally be co-supervised by Prof Gareth Jones at DCU.

Federated Meta-Learning: Democratizing Algorithm Selection, Meta-Learning, and Automated Machine Learning
“Federated Meta-Learning” is a novel concept with the key idea being a central repository (e.g. OpenML) that collects meta-information about how algorithms perform on datasets (only meta-information, not the models or datasets themselves). On this data, a deep meta-learning algorithm is trained as a “recommender system for algorithms”. Machine learning libraries such as (auto-)scikit-learn, (Auto-) Weka,… could then request recommendations for algorithms (and configurations) from e.g. OpenML via an API, and could contribute further meta information to the repository. This project involves work with the latest AutoML and algorithm-selection libraries, APIs, and deep learning. I would aim at integrating your work into real applications. Several of my colleagues, who work e.g. for OpenML, AutoWeka, and Auto-sklearn have already indicated their interest.

Beside my two projects there are, of course, plenty of other interesting PhD projects focusing on artificial intelligence, machine learning, automated machine learning (AutoML), meta-learning, algorithm selection, recommender systems (RecSys), natural language processing (NLP), information retrieval (IR), augmented reality (AR), virtual reality (VR), and many topics more.

The PhD stipends are placed at Ireland’s premier universities – in my case at Trinity College Dublin (TCD), but there are also supervisors at Dublin City University (DCU), University College Cork (UCC), NUI, Galway, University of Limerick, University College Dublin (UCD), and more.

The first round of recruitment is about to start in a few weeks, and more information can be found at and . If you have a question on my two projects, feel free to contact me. For general questions on the application process, contact the CRTs. For regular updates, follow my Twitter account, or the accounts of the CRTs.

Joeran Beel

Please visit for more details about me.


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