Sort by
Refine Your Search
-
Listed
-
Country
- United States
- United Kingdom
- Germany
- Sweden
- France
- Belgium
- China
- Austria
- Canada
- Netherlands
- Poland
- Australia
- Denmark
- Spain
- Singapore
- Hong Kong
- Portugal
- United Arab Emirates
- Lithuania
- Czech
- Italy
- India
- Andorra
- Cyprus
- Ireland
- Luxembourg
- South Africa
- Croatia
- Latvia
- Romania
- Switzerland
- Greece
- New Zealand
- Norway
- Saudi Arabia
- Armenia
- Barbados
- Bulgaria
- Estonia
- Europe
- Indonesia
- Japan
- Malta
- Qatar
- Slovenia
- Worldwide
- 36 more »
- « less
-
Field
- Computer Science
- Medical Sciences
- Engineering
- Economics
- Biology
- Science
- Mathematics
- Business
- Social Sciences
- Education
- Arts and Literature
- Psychology
- Chemistry
- Humanities
- Linguistics
- Electrical Engineering
- Environment
- Materials Science
- Design
- Earth Sciences
- Physics
- Sports and Recreation
- Law
- Philosophy
- 14 more »
- « less
-
analytics (chromatography, Raman spectroscopy, Surface Plasmon Resonance, etc.) Data analysis Machine learning Additional Information Work Location(s) Number of offers available1Company/InstituteUniversité
-
to an advanced Laboratory Directed Research and Development (LDRD) project, "Machine Learning Steered EXAFS Fitting for Autonomous XAS Analysis," aimed at revolutionizing real-time analysis of X-ray Absorption
-
Advanced brain-computer interface School of Electrical and Electronic Engineering PhD Research Project Self Funded Dr Mahnaz Arvaneh Application Deadline: Applications accepted all year round
-
through applied research programmes. Faculty in the ICT Cluster undertake funded industry-relevant research, teach courses in Computer Science, Computer Engineering, Information Security and Software
-
Artificial Intelligence (AI) and Machine Learning (ML). In this position students will contribute to research projects in CKL and as part of their education, will also engage in a dedicated 6-months internship
-
applications for faculty positions in Computer Science. Faculty specialising in data science, machine learning (deep learning, reinforcement learning, multimodal learning), Generative AI, and computer graphics
-
with the CDT’s aim to achieve a sustainable wind farm lifecycle by developing methods for high-value reuse of composite turbine blades. Machine learning and non-destructive evaluation techniques will be
-
in autonomous systems such as ground and aerial vehicles, and mobile robots. This includes: formulating and solving long-standing multiterminal information theory problems using modern machine learning
-
applications. The project integrates: Computational Fluid Dynamics (CFD) and multiphase flow modeling Radiative heat transfer Machine learning and reduced-order modeling Data-driven optimization for industrial
-
, biodiversity monitoring, and climate resilience. The work supports strategic priorities in Environmental Sciences, Software/Cyber. PhD researchers will explore how AI-driven Earth observation, computer vision