Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Leiden University
- University of Amsterdam (UvA)
- Harvard University
- Leiden University; Leiden
- Radix Trading LLC
- University of Amsterdam (UvA); Amsterdam
- University of Amsterdam (UvA); yesterday published
- AALTO UNIVERSITY
- BCBL - Basque Center on Cognition, Brain and Language
- BCBL BASQUE CENTER ON COGNITION BRAIN AND LANGUAGE
- CNRS
- Charles University, Faculty of Mathematics and Physics
- Eindhoven University of Technology (TU/e)
- KU LEUVEN
- La Trobe University
- Leibniz
- NOVA.id.FCT- Associação para a Inovação de Desenvolvimento da FCT
- Nature Careers
- Tallinn University of Technology
- Technische Universität Berlin •
- Universidade de Coimbra
- Universiteit van Amsterdam
- University of Birmingham
- University of Bonn •
- University of Leeds
- University of Luxembourg
- University of Miami
- University of Primorska
- University of Southern Queensland
- Uppsala universitet
- Warsaw University of Technology
- 21 more »
- « less
-
Field
-
30 Aug 2025 Job Information Organisation/Company Eindhoven University of Technology (TU/e) Research Field Computer science » Cybernetics Computer science » Programming Mathematics » Algebra
-
This PhD project is at the intersection of electromagnetism, numerical methods, and high-performance parallel computing, with application towards the design and optimisation of integrated circuits
-
achieving lower system costs. More information on the project: https://radarmimo.com/4d-imaging-automotive-mimo-radar/ The selected PhD candidate will work on one of the following research topic: Optimal
-
Summary Electrical machines are the workhorses of modern industry. Thus, electrical machines are facing challenges in meeting very demanding performance metrics, for example, high specific power
-
using tools from mathematical machine learning theory to prove mathematical guarantees about the performance of such new explanation methods, as well as programming to test out the methods and
-
investigate online feature engineering, continual learning and uncertainty quantification. Balance performance with governance. Projects will evaluate risk-adjusted returns alongside interpretability
-
methods. This will involve using tools from mathematical machine learning theory to prove mathematical guarantees about the performance of such new explanation methods, as well as programming to test out
-
theory to prove mathematical guarantees about the performance of such new explanation methods, as well as programming to test out the methods and mathematical theory in experiments. (See example references
-
, fundamentally limiting their ability for spatial reasoning, temporal logic, and operating in low-resource scenarios, which leads to shortcut learning and hallucination at test-time. This PhD project focuses on a
-
are critically hindered by the language-focussed optimization of current foundation models, fundamentally limiting their ability for spatial reasoning, temporal logic, and operating in low-resource scenarios