Sort by
Refine Your Search
-
candidate with a completed Master’s degree in Chemistry, Chemical Engineering, Materials Science or a related field. Candidate should have an affinity for multidisciplinary fields of research and a hands-on
-
Chemical/Environmental Engineering, Microbiology or Bioinformatics Demonstrable background and strong interest in biological processes and biotechnologies Independent, self-motivated, curiosity-driven mind
-
of computational tools in order to help with the energy transition. The successful candidate holds a MSc. degree in computational science, applied physics, mechanical engineering, chemical engineering or a similar
-
position is part of the ERC Starting Grant VenusVolAtmos, in which we aim to constrain the chemical links and feedback mechanisms between Venus' interior, surface an atmosphere, both experimentally and
-
& Technology, Nanoscience, Chemical Engineering, Radiation Science & Technology, and Engineering Physics. We are also training the next generation of high school teachers. Click here to go to the website
-
, Chemical Engineering, Radiation Science & Technology, and Engineering Physics. We are also training the next generation of high school teachers and science communicators. Click here to go to the website
-
research component. Our scientists conduct ground-breaking fundamental and applied research in the fields of Life and Health Science & Technology, Nanoscience, Chemical Engineering, Radiation Science
-
Reflectance spectroscopy is a technique widely used in planetary sciences to investigate the chemical composition, texture, temperature and physical parameters of the studied planetary body. In
-
, Nanoscience, Chemical Engineering, Radiation Science & Technology, and Engineering Physics. We are also training the next generation of high school teachers. Click here to go to the website of the Faculty
-
combine chemical process engineering knowledge with data-driven approaches in an effective way. The methods that you will develop and apply can potentially include hybrid modeling, graph neural networks