130 machine-learning-"https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" "UCL" positions at DAAD
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
group has used their expertise in computer simulations on small model chromosomes to demonstrate that polymer-assisted condensates are capable of maintaining the epigenetic state through 40 generations
-
to application at http://www.kseta.kit.edu/application.php . Further information about the KSETA Europe application procedure, available research topics, subjects for doctoral dissertations and the KSETA
-
. Only online applications will be accepted. AVAILABLE PROJECTS: Nanoscience: Application of bistable DNA devices Nanoscience: Synthesis of Carbon-Nanostructures on Inert Surfaces Biophysics: Learning
-
metamaterials. The successful candidate participates actively in the qualification program and general scientific activities of D³. More information can be found at https://tu-dresden.de/ing/forschung
-
of industrial processes. In a joint effort of both institutes, the Department AI4Quantum – Machine Learning for Quantum Simulation and Computing and Thermal Energy and Process Engineering are looking for a PhD
-
research with the combined tools of immunology, microbiology, virology, cell biology and molecular biology. For more information, please see https://www.mhh.de/hbrs/zib MD/PhD Molecular Medicine
-
Description For our location in Hamburg we are seeking: Doctoral Researcher in Machine Learning and Data Processing in the Field of Seismic Measurements Remuneration Group 13 | Limited: 3 years
-
this with expertise in high-performance computing and artificial intelligence using unique scientific infrastructures. Are you excited about working at the interface of natural and computer sciences? At
-
learning new techniques The University of Regensburg aims to increase the proportion of women and therefore explicitly encourages qualified women to apply. The University of Regensburg is particularly
-
and training provision within CAFE-BIO are available from the network website ( https://cafe-bio.org ) and the official EU page for the network ( https://cordis.europa.eu/project/id/101226762