21 machine-learning-phd positions at University of Twente (UT)

PhD Position in Machine Learning for Digital Fincance

total. In your project, you will do research on and apply machine learning techniques to make a real-world impact in academia and at financial institutions. A potential research topic is the design of

PhD Position in Machine Learning for Green Credit Scores

/en/339893/phd-position-in-machine-learning-for… Contact City Enschede Website http://www.universiteittwente.nl/ Street Drienerlolaan 5 Postal Code 7522 NB STATUS: EXPIRED

PhD position on analysis of geometric machine learning methods

answering mathematical questions. You have a solid background in one or more of the following: functional analysis, numerical analysis, differential geometry, theoretical machine learning. You are motivated

PhD position on Sparse Training for Deep Reinforcement Learning

present research findings in top-tier conferences (e.g., Machine Learning, JMLR) and journals (e.g., NeurIPS, ICLR, ICML, IJCAI, AAMAS, ECMLPKDD). Collaborate with a international team of researchers and

PhD position on Sparse Training for Energy-Efficient Deep Learning

methods to scale up deep learning. Publish and present research findings in top-tier conferences (e.g., NeurIPS, ICLR, ICML, IJCAI, AAMAS, ECMLPKDD) and journals (e.g., Machine Learning, JMLR). Collaborate

PhD position on Robust, Generalizable AI for Medical Imaging

in their work, facilitating the analysis of medical images and other data, for more rapid, comprehensive and accurate diagnosis, guidance of surgeries and more. Today, deep learning methods

PhD position on Calibration in Deep Learning for Zero Downtime in Cyber-Physical Systems

to staff position within a Research Infrastructure? No Offer Description The vacancy is focused on calibration in deep learning. Deep Neural Networks (DNNs) have demonstrated significant predictive

DC04: Towards a unified constitutive model for saturated granular fluids and solids

to staff position within a Research Infrastructure? No Offer Description We are seeking a full time PhD researcher with interests in granular physics, continuum mechanics and computer modelling to join

Postdoc position on Scalable Energy-Efficient Deep Learning

. Publish and present research findings in leading scientific journals (e.g., Machine Learning, JMLR) and conferences (e.g., NeurIPS, ICLR, ICML, IJCAI, AAMAS, ECMLPKDD). Contribute to the mentoring

PhD position in Optimization, Optimal Transport and Inverse Problems

) and Wasserstein Gradient Flows, and their applicability to solve inverse problems and design infinite-dimensional machine learning algorithms. The goal of this project is the analysis of dynamic