Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
Michael Bronstein, AITHYRA Scientific Director AI and Honorary Professor of the Technical University of Vienna in collaboration with Ismail Ilkan Ceylan, expert in graph machine learning, invites
-
computational framework, integrated with deep reinforcement learning (DRL) methodologies for both gene-level and edge-level perturbation control, represents a significant advancement in the computational toolkit
-
of termination, with a major focus on quality control processes, including mRNA surveillance and ribosome-associated quality control. Required qualifications include a Ph.D. in Molecular Biology/Molecular
-
Post-doctoral Research Fellow Level 1 or 2 in Microbiology Imaging, UCD School of Chemical and Bioprocess Engineering, 18 months Applications are invited for a temporary post of a Post-doctoral
-
Postdoc "Interferometric SAR Data Processing and Analysis for Implementation in the 3D-ABC Founda...
remote sensing SAR image sets Experience in programming and in automation of image data processing Interest in the development of interferometric SAR data sets for large-scale AI and FM training Basic
-
feed processing. For non-Scandinavian candidates an effort to learn to read, write, and speak Danish is a requirement. Contact Further information on the position may be obtained from Professor Jan Værum
-
and explainable hybrid Artificial Intelligence, i.e., the mix of formal knowledge representation and reasoning with sub-symbolic data-driven machine learning approaches, to work on car-driver digital
-
have experience in computational neuroscience and data mining using machine learning methods. The successful candidate will lead an independent research project dedicated to identifying abnormal neuronal
-
Neurobiologie (ZMNH) Main tasks You will join the Institute of Medical Systems Biology and the bAIome Center for Biomedical AI (baiome.org) to complement our lively and enthusiastic team of machine learning and
-
and analysis of mathematical methods for novel imaging techniques and foundations of machine learning. Within the project COMFORT (funded by BMFTR) we aim to develop new algorithms for the training