Sort by
Refine Your Search
-
Category
-
Employer
-
Field
-
is focused on enabling applications through a fundamental understanding of material formation processes and properties. KU Leuven (University of Leuven) has been a center of learning for nearly six
-
onboarding period that includes specialized courses and hands-on training in AI and machine learning. You'll also have the chance to explore different labs and core facilities, meet fellow researchers, and
-
The Faculteit Geneeskunde en Farmacie, Department Basis (bio)-medische wetenschappen, Research Group Genetics Reproduction and Development is looking for a PhD-student with a doctoral grant. More
-
looking for a dynamic and highly motivated PhD student. Research topic Whereas mutations are the driving force for adaptive evolution, many genetic alterations exert negative fitness effects. The effect
-
different stages of the cell cycle (Vukašinović and Hsu et al., 2025, Cell). We are looking for a motivated PhD student to investigate how hormonal signals are integrated and coordinated to control the plant
-
The Brussels School of Governance, Department Instituut voor Europese Studies, is looking for a PhD-student with a doctoral grant. More concretely your work package, for the preparation of a
-
The Faculty Social Sciences & Solvay Business School, Department Sociologie, Research Group Brussels Institute for Social and Population Studies is looking for a PhD-student with a doctoral grant
-
regulatory network reconstruction and wide range of machine learning approaches The host labs will provide financial support for the whole length of the PhD. The applicant will be expected to seek independent
-
the ITN network. Terms of employment We offer a PhD position within our groups at KU Leuven, situated within the broader ITN network. Application procedure For more information please contact Prof. dr
-
-type specific samples, state-of-the-art molecular biology techniques, multimodal data generation and integration, gene regulatory network reconstruction and wide range of machine learning approaches