Sort by
Refine Your Search
-
Category
-
Country
-
Employer
- University College Cork
- Aarhus University
- Argonne
- Chalmers University of Technology
- Cornell University
- RIKEN
- Technical University of Munich
- University of Exeter
- University of Helsinki
- ; Xi'an Jiaotong - Liverpool University
- Aalborg University
- Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID
- Baylor University
- Brookhaven National Laboratory
- Chalmers University of Technology
- Charles University
- Christian-Albrechts-Universitaet zu Kiel
- Delft University of Technology
- Delft University of Technology (TU Delft)
- Eindhoven University of Technology
- Eindhoven University of Technology (TU/e)
- Forschungszentrum Jülich
- Inria
- Karlstad University
- Karolinska Institutet
- Karolinska Institutet (KI)
- Max Planck Institute for Gravitational Physics, Potsdam-Golm
- Nencki Institute of Experimental Biology
- Oak Ridge National Laboratory
- Stony Brook University
- Texas A&m Engineering
- Umea University
- University of London
- University of Nevada, Reno
- University of Oregon
- University of Oxford
- XIAN JIAOTONG LIVERPOOL UNIVERSITY (XJTLU)
- 27 more »
- « less
-
Field
-
in modeling, analysis and control of electric power distribution and transmission system, applying state of the art machine learning (ML) and deep learning algorithms to develop cybersecurity
-
Researcher to join the Machine Learning in Biomedicine group, in collaboration with the Precision Cancer Epigenomics group at NCMM, through the NORPOD program. Summary of the project Human tumors
-
candidate to have a PhD degree from a relevant field with skills and experience in image analysis and machine learning. Familiarity with the volumetric microscopy image data and statistical methods
-
with mathematical modeling and machine learning methods will ultimately allow us to predict the entire recognition space for any given TCR sequence. Our work is embedded into close collaborations with
-
development, employing machine learning techniques applied to industrial datasets, and in collaboration with industry. The applicant will work in the Software Engineering Theme, which is one of several Themes
-
to different domains. Specifically, you will: Develop, implement, and refine Machine Learning (ML) techniques for self-supervised Deep Learning (DL) for scientific and large-scale datasets Implement parallel ML
-
must have concluded a PhD in Computer Science, Data Science, Artificial Intelligence, Computer Engineering or related area (essential). • The candidate should have a background Data Science/Machine
-
We are seeking to appoint a Research Associate in AI with a specialism in Deep Learning. The Research Associate will engage in internationally leading research in the development of AI and machine
-
the limits of the scale in force. Mission confiée The main objective of this project is the understanding and development of robust and effective stochastic optimization methods for training deep learning
-
. ● Coding capability in one of the major languages. ● Experience in machine learning and deep learning and their applications in solving geophysical problems. ● Ability to effectively collaborate in a