Postdoc / Research Engineer Opportunity at James Cook University – AI for Aquaculture
Postdoc / Research Engineer Opportunity at James Cook University – AI for Aquaculture
We're looking for a Postdoctoral Researcher or Research Engineer (Level A-B) to develop deep learning solutions for Aquaculture at James Cook University.Start: Immediately Duration: 1 year (extension possible)If you have … Read More Read More
Categories:
🚀 Fully Funded PhD Opportunity in Software Engineering for Artificial Intelligence (SE4AI) at Trent University
🚀 Fully Funded PhD Opportunity in Software Engineering for Artificial Intelligence (SE4AI) at Trent University
I am looking for a PhD student to join a research project in Software Engineering for Artificial Intelligence (SE4AI), hosted and led by a colleague at ÉTS Montreal. At this … Read More Read More
Categories:
Prompt Learning for Video Anomaly Detection
Prompt Learning for Video Anomaly Detection
About the Project Video Anomaly Detection (VAD) is a critical task in video surveillance and auditing, aiming to automatically identify abnormal events within video streams. However, many video platforms still … Read More Read More
Categories:
Machine Unlearning for Privacy-Preserving Cross-Modal Retrieval Systems (Ref: CO/GC-SF6/2025)
Machine Unlearning for Privacy-Preserving Cross-Modal Retrieval Systems (Ref: CO/GC-SF6/2025)
About the Project This PhD project addresses the critical challenge of selective information removal and privacy preservation within cross-modal retrieval systems. Contemporary cross-modal architectures require effective mechanisms to selectively forget … Read More Read More
Categories:
Semantic-Aware Data Deduplication for Efficient and Reliable Machine Learning Training (Ref: CO/GC-SF7/2025)
Semantic-Aware Data Deduplication for Efficient and Reliable Machine Learning Training (Ref: CO/GC-SF7/2025)
About the Project The exponential growth of training datasets in machine learning, particularly in natural language processing (NLP), has highlighted the critical challenge of data duplication. Duplicate or near-duplicate content, … Read More Read More
Categories:
Neural Machine Unlearning for Privacy-Preserving Information Retrieval: Novel Methods and Corrective Mechanisms (Ref: CO/GC-SF5/2025)
Neural Machine Unlearning for Privacy-Preserving Information Retrieval: Novel Methods and Corrective Mechanisms (Ref: CO/GC-SF5/2025)
About the Project This PhD project addresses the critical challenge of machine unlearning within neural information retrieval (NIR) systems. Contemporary NIR architectures require effective mechanisms to selectively remove specific data … Read More Read More
Categories:
Developing Continual Adaptive Learning Techniques for Large Language Models in Neural Information Retrieval (Ref: CO/GC - SF4/2025)
Developing Continual Adaptive Learning Techniques for Large Language Models in Neural Information Retrieval (Ref: CO/GC - SF4/2025)
About the Project This PhD project investigates the critical challenge of catastrophic forgetting in neural information retrieval (NIR) systems. Contemporary NIR architectures exhibit significant performance degradation when integrating new information … Read More Read More
Categories:
Responsible AI and Digital Twins for Sustainable Biodiversity Net Gain
Responsible AI and Digital Twins for Sustainable Biodiversity Net Gain
About the Project The increasing generation, adoption and deployment of Artificial Intelligence (AI) technologies that could impact humanity, heritage and environment raise continuously interests and also concerns from general public, … Read More Read More
Categories:
Query Performance Prediction Combining Traditional and Neural Information Retrieval Models
Query Performance Prediction Combining Traditional and Neural Information Retrieval Models
About the Project In the field of information retrieval (IR), query performance prediction (QPP) aims to predict the effectiveness of a system for a given search query without resorting to … Read More Read More
Categories:
Shrinking LLMs using Principled Training Approaches
Shrinking LLMs using Principled Training Approaches
About the Project Large Language Models (LLMs) are machine learning models trained to perform general-purpose tasks that can be modeled using text, images, or both. They showcase emerging abilities that … Read More Read More
Categories: