Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- NTNU - Norwegian University of Science and Technology
- NTNU Norwegian University of Science and Technology
- Eindhoven University of Technology (TU/e)
- Aalborg University
- University of Twente
- Aalborg Universitet
- Forschungszentrum Jülich
- Leiden University
- Technical University of Denmark
- ;
- CNRS
- Chalmers University of Technology
- Cranfield University
- Delft University of Technology (TU Delft)
- Erasmus University Rotterdam
- Fundació per a la Universitat Oberta de Catalunya
- Max Planck Institute for Biogeochemistry, Jena
- Nature Careers
- Queensland University of Technology
- Tampere University
- Technical University of Munich
- The University of Manchester
- Ulm University •
- University of Amsterdam (UvA)
- University of Antwerp
- University of Cyprus
- University of Southern Denmark
- University of Texas at El Paso
- Université de Liège
- cellumation GmbH
- 20 more »
- « less
-
Field
-
24th April 2026 Languages English English English The Department of Mathematical Sciences has a vacancy for a PhD Candidate in Mathematical Foundations of Machine Learning for Sequential Data Apply
-
knowledge for a better world. You will find more information about working at NTNU and the application process here. About the position Distributed machine learning takes advantage of communication and
-
24th April 2026 Languages English English English The Department of Electronic Systems has a vacancy for a PhD Candidate in Distributed Machine Learning Apply for this job See advertisement This is
-
learning from sequential data is available at the Department of Mathematical Sciences at the Norwegian University of Science and Technology (NTNU) in Trondheim. The project will be supervised by Prof
-
Deep Learning (CIDL), part of the Leiden Institute of Advanced Computer Science (LIACS). As a team, we develop cutting-edge techniques for advanced computational imaging systems, combining expertise from
-
Digital. The research focuses on advanced signal analysis and machine learning methods that enable robust operation and service continuity in future wireless networks under challenging radio conditions. As
-
Digital. The research focuses on advanced signal analysis and machine learning methods that enable robust operation and service continuity in future wireless networks under challenging radio conditions. As
-
activities Engage in international activities such as conferences and/or undertake research stays at foreign educational institutions Teaching and supporting of learning activities in courses related
-
. You will become part of a dynamic, collaborative working environment with expertise in drilling engineering, geomechanics, machine learning, and energy systems. The project will integrate real‑time
-
-design with accelerators (FPGAs, GPUs, near-memory systems) to achieve real-time, energy-efficient AI for high-tech industry applications. Work with leading companies like ASMPT and shape the future of AI