Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- United Kingdom
- Sweden
- Germany
- Netherlands
- Portugal
- Spain
- France
- Singapore
- Norway
- Denmark
- United Arab Emirates
- Belgium
- Switzerland
- China
- Australia
- Poland
- Finland
- Italy
- Luxembourg
- Austria
- Canada
- Hong Kong
- Morocco
- Vietnam
- Ireland
- Romania
- Czech
- Japan
- Estonia
- Greece
- Brazil
- Cyprus
- Saudi Arabia
- Croatia
- Lithuania
- Andorra
- India
- South Africa
- Taiwan
- Malta
- New Zealand
- Slovenia
- Worldwide
- Hungary
- Israel
- Kenya
- Latvia
- 38 more »
- « less
-
Program
-
Field
- Computer Science
- Medical Sciences
- Economics
- Engineering
- Biology
- Science
- Business
- Mathematics
- Education
- Psychology
- Materials Science
- Earth Sciences
- Chemistry
- Arts and Literature
- Social Sciences
- Environment
- Humanities
- Linguistics
- Electrical Engineering
- Sports and Recreation
- Law
- Physics
- Philosophy
- Design
- Statistics
- 15 more »
- « less
-
the beginning and there is still much to be learned! You will lead a project that centers on how tactile end organs assemble, function, and recover after injury. You will be using non-standard animal models
-
automates building and modifying surface structures, submitting DFT calculations, post-processing electronic structure and vacancy energies, and extracting machine-learning descriptors for modeling oxygen
-
algorithms and routines for image processing, image reconstruction and enhancement, deep learning model training and inference, explainability/visualization, and statistical analysis of AI performance. Conduct
-
combining advances in Physics-Informed Machine Learning (PIML) and Graph Neural Networks (GNNs) with real-world energy applications, the project aims to better capture the dynamics of urban infrastructures
-
, and advanced machine learning in the engineering domain. Generative AI substantially changes the way engineers interact with and benefit from AI and access domain-specific knowledge, marking a phase
-
storage, but their widespread deployment is limited by challenges in energy density, stability, solubility, and cost of electroactive redox compounds. The PhD candidate will develop and apply machine
-
component disciplines; in explainable multi-modal deep learning models, in causal statistical models and in human-machine teaming and AI ethics. The researcher will conduct internationally-leading research in
-
inference, and Machine Learning methods. In addition to leading their own research projects, the appointed candidate will have the opportunity to contribute to the projects of PhD students in the group, as
-
& instructional materials for different learning styles * incorporating, as pedagogically appropriate, current technology in classroom, distance learning and laboratory environments * creating and modeling a
-
seminars, MA seminars and/or specialist classes. The selected candidate is expected to teach courses on topics in the field of quantitative finance, machine learning and data science. Courses should be