Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Radboud University
- Utrecht University
- University of Twente
- Eindhoven University of Technology (TU/e)
- European Space Agency
- Erasmus University Rotterdam
- European Magnetism Association EMA
- Maastricht University (UM)
- Naturalis
- Radboud University Medical Center (Radboudumc)
- Radboudumc
- The Open Universiteit (OU)
- University of Amsterdam
- University of Groningen
- Vrije Universiteit Amsterdam
- Vrije Universiteit Amsterdam (VU)
- 6 more »
- « less
-
Field
-
PhD position: Develop Hybrid Machine Learning for Global Soil Mapping Faculty: Faculty of Geosciences Department: Department of Physical Geography Hours per week: 36 to 40 Application deadline: 6
-
reactions. (2) Prof. Francesca Grisoni ( https://molecularmachinelearning.com/ ) leads the Molecular Machine Learning Group at the Technical University Eindhoven and will lead a project on designing
-
researchers across the ACT to identify emerging theoretical challenges motivated by astrodynamics, optimisation, control, scientific machine learning, mission design and autonomous systems, translating
-
and decision-making. Working with real-world data from Alliander, you will publish at leading machine learning venues while building tools with tangible impact on the Dutch energy sector. The Dutch
-
demonstrated its potential to support people with limited arm and shoulder function. Your task will be to explore and develop an AI-enhanced Human-Machine Interface (HMI) that enables a more intuitive and
-
information systems. The work sits at the boundary of machine learning and quantum computation, addressing how quantum devices can remain robust and reliable when operating under real-world noise conditions
-
primarily focus on computer vision and machine learning. You will develop and evaluate AI-driven visual speech recognition models and contribute to their integration into a smart-glasses prototype. The
-
plant growth, physiology and disease development; profile root and leaf microbiomes using amplicon sequencing; analyse integrated microbiome and phenotyping datasets; contribute to machine-learning
-
functioning in children. Childhood cognitive development shapes health and success later in life, understanding how environmental risk factors alter children's brain function, learning and behaviour
-
characterize subsurface structures, buried infrastructure, and material properties; · develop and apply AI and machine learning methods for signal processing, image analysis, data fusion, and prediction