13 data-"https:" "https:" "https:" "https:" "https:" "https:" "KU LEUVEN" PhD positions at Vrije Universiteit Brussel
Sort by
Refine Your Search
-
Listed
-
Category
-
Field
-
, require optical microscopes that can capture spatial and spectral information simultaneously, while remaining fast, data-efficient, and suitable for in-situ use. However, conventional hyperspectral
-
training (ST) can counter inflammation and improve immune function in older persons with different levels of systemic inflammation. In this new FWO-funded project (https://researchportal.vub.be/en/projects
-
. More information can be found on our website: https://www.b-phot.org . The candidate will be supervised by Prof. Francis Berghmans, and co-supervised by Dr. Sidney Goossens and Dr. Sergei Mikhailov
-
, and human geographers. Its members conduct research on the socioeconomic, cultural, and demographic dimensions of patterns of social inequality within Belgium, Europe, and beyond. For more information
-
of precipitation on blade erosion You will work on the ACCEMO project in collaboration with KU Leuven, who will deliver insights on the effect of climate change on meteorological conditions at various locations
-
8 Dec 2025 Job Information Organisation/Company Vrije Universiteit Brussel Department imec-SMIT Research Field Communication sciences » Media studies Researcher Profile First Stage Researcher (R1
-
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
-
holography to ultra-wide-angle, ultra-high-resolution holography presents significant challenges. These include enormous data bandwidths, sophisticated optical control, advanced rendering pipelines, and new
-
statistics. You will also collect data independently, conduct surveys and organise workshops with companies, policymakers and academics, under the supervision of two academic promoters. In addition, you will
-
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