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<p class="p1"><span class="s1"><b>Location</b>: Cardiff, UK</span><o:p></o:p></p>
<p class="p1"><span class="s1"><b>Deadline for applications</b>: 4th June</span><o:p></o:p></p>
<p class="p1"><span class="s1"><b>Start date</b>: 1st September 2025 (or as soon as possible thereafter)</span><o:p></o:p></p>
<p class="p1"><span class="s1"><b>Duration: </b>36 months</span><o:p></o:p></p>
<p class="p1"><span class="s1"><b>Keywords</b>: graph neural networks, explainable AI, compositional generalisation</span><o:p></o:p></p>
<p class="p2"><o:p> </o:p></p>
<p class="p1"><span class="s1"><b>Details about the post</b></span><o:p></o:p></p>
<p class="p1"><span class="s1">Applications are invited for a Postdoctoral Research Associate post in the Cardiff University School of Computer Science & Informatics, to work on the InteGraL project (“Interpretable Graph-Based Machine Learning”). This Leverhulme
Trust funded project is focused on developing alternatives to Graph Neural Networks (GNNs). Its central aim will be to introduce methods that are interpretable by design, while at the same time being more robust than GNNs and generalising better to problem
instances that are out of the training set distribution. The models will be applied to problems in Natural Language Processing and Computational Chemistry, among others. More details about the post and instructions on how to apply are available at
<a href="https://www.jobs.ac.uk/job/DMZ697/research-associate">https://www.jobs.ac.uk/job/DMZ697/research-associate</a></span><o:p></o:p></p>
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