Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
- Computer Science
- Medical Sciences
- Economics
- Engineering
- Biology
- Science
- Business
- Education
- Psychology
- Mathematics
- Social Sciences
- Chemistry
- Materials Science
- Environment
- Humanities
- Earth Sciences
- Electrical Engineering
- Arts and Literature
- Linguistics
- Physics
- Design
- Philosophy
- Law
- Sports and Recreation
- 14 more »
- « less
-
Vision, Robotics, Evolutionary Computation, Deep Reinforcement Learning, and Machine Learning. This should include a proven publication track record. You should also have: Research Associate: A PhD (or
-
monitoring and health monitoring of the different machine components. To this end, multiple dedicated measurement campaigns have been performed throughout the Belgian offshore zone, resulting in a large in
-
Associate: A PhD (or equivalent) in an area pertinent to the subject area, i.e. Computer Science, Machine Learning, Robotics. Research Assistant: A Master’s degree (or equivalent) in an area pertinent
-
have a PhD in Civil Engineering, Engineering Mechanics, or Mechanical Engineering. Applicants are expected to demonstrate research experience in the fields of structural modeling and machine-learning
-
of this project will bring forward the integration of novel methods at the intersection of advanced control, optimization, manufacturing science, robotics, and machine learning. The doctoral student position we
-
workstreams, and the PhD’s will be working along senior staff to perform tasks in different workstreams, in strong collaboration with multiple international partners and fellow PhDs from all over the world. Key
-
dynamics, data science, and machine learning are beneficial. What we offer: We offer a position with a competitive salary in one of Germany’s most attractive research environments. TUD is one of eleven
-
Methodology The PhD candidate will develop innovative AI models using machine learning and deep learning frameworks. Methodologies will include supervised and unsupervised learning approaches to identify and
-
2025. Encouraged by the continuing success of modern machine learning (ML) techniques, researchers have become ambitious to develop ML solutions for challenging science and engineering problems with
-
will be adapted to the candidate’s background and the evolving needs of the center. Possible directions include the application of rock physics models, Bayesian inversion methods, and machine learning