We are establishing a new research group, focusing on probabilistic machine learning with applications to speech (audio) and theoretical (statistical) physics, at KU Leuven. We are focusing on uncertainty estimation and generative AI, both of which are active areas of research today. When AI models estimate uncertainty (or a posterior distribution, rather than a point estimate) while making predictions, they become more trustworthy and efficient. For instance, instead of transcribing an audio snippet as “this talk”, a speech recognition model could transcribe it as “this talk (60% confidence)” and “the stock (30% confidence)”. We also develop efficient sampling methods for high-dimensional systems using flow-based methods.
We are seeking a highly motivated PhD candidate who can bridge cutting-edge probabilistic ML research with impactful real-world applications — someone who deeply understands theoretical advances and brings creativity and practical skills to identify, design, and implement compelling use cases.
The positions can start immediately, and positions will be filled as soon as suitable candidates are found. Interested PhD candidates should submit their CV, transcripts, contact information for 2 or 3 referees, and a motivation letter (max 1-page) here. The motivation letter should clearly outline the interest in probabilistic ML and its applications, as well as any possible past experience in AI and related fields such as speech/physics.
Apply here. For more information, please contact Prof. Dr. Vipul Arora, mail: vipul.arora@kuleuven.be (please put [PhD application] in the subject of the email)