Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
- Computer Science
- Engineering
- Economics
- Materials Science
- Medical Sciences
- Biology
- Chemistry
- Mathematics
- Arts and Literature
- Electrical Engineering
- Psychology
- Education
- Linguistics
- Physics
- Business
- Humanities
- Science
- Philosophy
- Earth Sciences
- Law
- Social Sciences
- Sports and Recreation
- 12 more »
- « less
-
of such program could be done in case of it was necessary. For instance, for the linkage of new material models or certain numerical features such as a new finite element. This research will benefit from excellent
-
Neuro-Symbolic Methods for Explanation-Based Reasoning with Large Language Models
-
the machining induced damage in a MMC and its service life using experimental and numerical methods Funding Notes 1st or 2:1 degree in Engineering, Materials Science, Physics, Chemistry, Applied Mathematics
-
to basis set size. We are working on methods that will allow us to solve the time-dependent Schrödinger equation more quickly. In this project you will develop new (parallel) methods based around accelerated
-
demonstrate good knowledge of mathematics, numerical modelling, fluid dynamics and signal processing and be a proficient user of a programming language, e.g. Python or Matlab. Main duties and responsibilities
-
for classical imagery inspections (e.g. CCTV) in sewer pipes treated with CIPP lining employing powerful semi-analytical and hybrid (numerical+analytical) acoustic simulations. During the project lifetime
-
Artificial intelligence and machine learning methods for model discovery in the social sciences School of Electrical and Electronic Engineering PhD Research Project Self Funded Prof Robin Purshouse
-
of parallel computing (GPUs) to speed solution within the optimisation process. Funding Notes 1st or 2:1 degree in Engineering, Materials Science, Physics, Chemistry, Applied Mathematics, or other Relevant
-
with career stage). Essential Interview / Application / Test In-depth knowledge of Computational Intelligence/Machine Learning systems and methods, in particular those relevant to Explainable AI, Physics
-
of numerical methods for solving scattering problems and inverse problems (assessed at: application and interview) Proficiency in scientific programming languages, Julia or Python (assessed at: application and