25 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"SUNY" scholarships in Belgium
Sort by
Refine Your Search
-
intelligence, machine learning and data science. You will play an active role in the research team, publish papers, take part in workshops, public events and other activities. The candidates should have a
-
, scale and resolution in which in vivo pathways of immune cells can be unraveled. Furthermore, it provides a goldmine for training causal machine learning models to move towards precision medicine
-
children learn new words not only by listening to a storyteller but also by processing multimodal signals such as iconic gestures and gaze direction. Using eye-tracking in both real-life and digital contexts
-
teacher education. Using Teach for All as a case-study, the project aims to better understand how and why education polices travel across time and space. While policy mobility is driven by a wide range of
-
. More concretely your work package, for the preparation of a doctorate, contains: Shape the future of immersive visual technologies through optical, computational, and machine‑learning innovation. We
-
defence of a PhD thesis focusing on machine learning-based forecasting of renewable energy production, with a particular focus on wind energy. The research will be conducted within the VLAIO ICON NEXT-WIND
-
approach, combining machine-learning–enhanced text-as-data analysis with qualitative discourse analysis. The project aims to produce a set of high-quality scholarly outputs, including peer-reviewed journal
-
fully funded PhD position in machine learning, AI, and data science for public health within the Electronics & Informatics Department (ETRO) of Vrije Universiteit Brussel (VUB). The PhD is embedded in
-
microkinetic modelling or/and machine learning, especially in the area of polymer design, is valued. Experience with modelling macromolecular structures or/and predicting polymer material properties is highly
-
of Applied Mathematics: Statistics Position You will work actively on the preparation of a PhD thesis in the field of statistics and machine learning. The envisioned topic is practical challenges of causal