Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- United Kingdom
- Germany
- Sweden
- Netherlands
- Denmark
- Norway
- Spain
- Belgium
- Portugal
- France
- Switzerland
- United Arab Emirates
- Australia
- Singapore
- Poland
- China
- Austria
- Hong Kong
- Luxembourg
- Vietnam
- Finland
- Canada
- Italy
- Estonia
- Romania
- Morocco
- Czech
- Ireland
- Cyprus
- Lithuania
- South Africa
- Brazil
- Croatia
- Greece
- India
- Latvia
- New Zealand
- Andorra
- Japan
- Saudi Arabia
- Slovenia
- Armenia
- Bulgaria
- Israel
- Kenya
- Malta
- Worldwide
- 38 more »
- « less
-
Program
-
Field
- Computer Science
- Engineering
- Medical Sciences
- Economics
- Science
- Biology
- Mathematics
- Chemistry
- Materials Science
- Electrical Engineering
- Arts and Literature
- Education
- Humanities
- Business
- Earth Sciences
- Social Sciences
- Linguistics
- Environment
- Psychology
- Design
- Philosophy
- Physics
- Law
- Sports and Recreation
- 14 more »
- « less
-
, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
-
twins, human-centric systems, robotics PhD-E: Optimizing Images Quality and Deep Learning Methods for Vineyard Disease Detection. PhD grantors: University Padova (IT) & Poznan University of Technology (PL
-
Novel routes for in-situ measurements during the manufacture of thin flexible electronic films. School of Chemical, Materials and Biological Engineering PhD Research Project Self Funded Prof
-
: Development of ML-based tools for analysis and engineering protein dynamics PhD enrolment: Czech Technical University in Prague DC14: Machine learning for Empirical Valence Bond (EVB) simulations to engineer
-
Automatization and Digital Enhancement of Characterisation Techniques: Joining the Dots between AI, Machine Learning and Materials Advances School of Chemical, Materials and Biological Engineering
-
, and evaluation The ideal candidate will lead their own project, and also collaborate with and support 1-2 PhD students on their projects. The ideal candidate will also be interested in learning to write
-
students who are prepared for a lifetime of learning and rewarding work. Candidates should hold a PhD or master’s degree in electrical and computer engineering or related fields and should be comfortable
-
of this PhD is to develop physics-informed neural operator frameworks that embed governing equations and invariants of fluid mechanics directly into learning architectures, enabling real-time, generalizable
-
schools in the world. For more details, please view https://www.ntu.edu.sg/mae/research . We seek a highly motivated Research Fellow to reverse engineer microstructured composite materials with novel
-
to staff position within a Research Infrastructure? No Offer Description PhD Position in Physics-Informed Machine Learning for Cardiac Magnetic Resonance The CMR Zurich group at the Institute