Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- UTB
- Tilburg University
- Helmholtz Association of German Research Centres
- Monash University
- Susquehanna International Group
- University of Sheffield
- Aalto University
- Chalmers University of Technology
- ETH Zurich
- Heidelberg University
- King's College London
- Nanyang Technological University
- SciLifeLab
- Stockholm University
- <span lang="en">German Center for Neurodegenerative Diseases (DZNE)</span>
- Aalborg University
- Aarhus University
- CEA
- EPFL
- European Space Agency
- Ghent University
- Heinrich Heine University Düsseldorf
- King Abdullah University of Science and Technology
- Linköping University
- Linnaeus University
- Max Planck Institute of Animal Behavior, Radolfzell / Constance
- Mälardalen University
- Raven51 AG (BAM)
- Technical University of Denmark
- Technical University of Denmark (DTU)
- Technische Universität Dresden (TU Dresden)
- The University of Southampton
- University of Copenhagen
- University of Gothenburg
- University of Helsinki
- University of Oslo
- University of Twente
- Vrije Universiteit Brussel
- Yale University
- 29 more »
- « less
-
Field
-
is a unified application form for all positions in the Beyesian Deep Learning group at KAUST led by Prof Maurizio Filippone, including Research Intern MS/PhD Student PhD Student Postdoctoral Fellow
-
Optimising treatment outcomes for pulmonary arterial hypertension using deep learning-based analysis of novel perfusion magnetic resonance imaging (S3.5-SMP-Sourbron) School of Medicine and
-
Primary supervisor Chern Hong Lim Co-supervisors Bisan Alsalibi Yasmeen George Research area Data Science and Artificial Intelligence While deep learning has shown remarkable performance in medical
-
Postdoc in AI-driven design of environment-responsive antibodies and nanobodies - DTU Bioengineering
will develop deep learning and generative models for binder design, work closely with wet lab scientists who express and test your designs, and collaborate with leading international partners. The
-
methods with a particular focus on deep learning and image analysis. The project relies on a close collaboration with researchers at the Department of Immunology, Genetics and Pathology (IGP) at Uppsala
-
. Research Aim This PhD research aims to develop and evaluate AI and Machine Learning approaches for early prediction, risk stratification and prognostic modelling of heart disease , with a focus on
-
. Research Aim This PhD research aims to develop and evaluate AI and Machine Learning approaches for early prediction, risk stratification and prognostic modelling of heart disease , with a focus on
-
protein engineering, computationally designing antibodies, nanobodies, and binding proteins with condition-dependent activity. You will develop deep learning and generative models for binder design
-
Helmholtz Association of German Research Centres | Geesthacht, Schleswig-Holstein | Germany | 2 months ago
data. Manage preferences for further information and to change your choices. Accept all cookies Reject optional cookies Skip to main content Postdoctoral Researcher - Probabilistic Deep Learning for
-
UTB | about 2 months ago
engineering of integrated circuits for hardware assurance and intelligence analysis. The project is conducted within the Deep Learning for Perception and Data Science, Safety and Security research units