This role involves analyzing large-scale security telemetry, threat intelligence feeds, and detection data to uncover patterns and support strategic initiatives. You will work cross-functionally with product and engineering teams to transform raw security data into actionable insights, using tools like SQL, Python, and Logscale.
This role involves analyzing large-scale security telemetry, threat intelligence feeds, and detection data to uncover patterns and support strategic initiatives. You will work cross-functionally with product and engineering teams to transform raw data into actionable insights, design dashboards, and maintain data pipelines.
This role involves working as a link between business users and technical teams to identify and solve process inefficiencies using technology, data, and AI. Responsibilities include documenting workflows, analysing data, and supporting the implementation of automation and technology solutions.
This role involves researching and developing AI/ML approaches for power electronics applications, designing and simulating power electronic converter systems, and optimizing converter design and performance. You will work closely with experienced engineers and researchers to translate academic research into practical engineering solutions, focusing on sectors like electric vehicles, rail, and renewable energy.
The role involves developing computer vision and machine learning techniques to process live streams of eSports events, identifying in-game events, and improving data quality for betting markets. The candidate will work with historical data, implement low-latency AI, and collaborate with a team familiar with multiple coding languages.
The PhD position involves conducting original research in Physical AI, focusing on vision-language-action models, world models and planning, and adaptation and edge intelligence. The candidate will join the A3 Lab, supervised by Associate Professor Behzad Bozorgtabar and co-supervised by Professor Qi Zhang, and will target publications at top-tier machine learning, computer vision, and robotics conferences.
This role involves leading research, teaching, and administration in the field of Human-AI teaming, focusing on how humans and AI can work together as integrated teams. You will collaborate with WMG and its partners on complex industrial problems in areas like autonomous transport, robotics, and health technology.
This role involves working between research and engineering teams to build performance models and calculators for AI infrastructure. You'll optimize GPU/accelerator code, profile real training and inference runs, and provide actionable insights that influence system architecture and procurement decisions for the organization and its members.
This role involves working alongside senior engineers to build performance models and calculators for AI infrastructure, predicting the efficiency and cost-effectiveness of different setups. You'll have real ownership and work with cutting-edge technologies like GPU code, profiling tools, and Python, while collaborating with a diverse group of experts in the AI field.
This PhD project focuses on developing a physics-informed AI framework for the design and optimization of alternative cooling technologies. The candidate will integrate thermodynamic modeling, machine learning, and multi-objective optimization, with opportunities to balance experimental and computational work based on their interests.
The role involves leading and developing applied AI in marketing, contributing to teaching and research, and supporting academic colleagues. The position is key to achieving AACSB accreditation and TEF Gold for the Liverpool Business School.
You will develop and optimize scalable library software for GPU and CPU accelerated data processing, focusing on numerical methods and performance tuning. You'll work closely with leadership and partners to understand requirements and contribute to technical roadmaps, providing technical guidance to your team.
You will develop and optimize scalable library software for GPU and CPU accelerated data processing, focusing on performance tuning and benchmarking. You'll work closely with leadership and partners to enhance library features and performance, contributing to NVIDIA's cutting-edge AI and HPC projects.
This role involves designing, building, and delivering cutting-edge GenAI and Agentic AI products. You will work within a product squad to develop multi-step workflows, optimize AI performance, and integrate various backend services, all while ensuring security and scalability on Azure.
This PhD studentship focuses on developing hybrid fault diagnosis methods for wind turbine generators by combining physical drivetrain models with AI-driven data analysis. The research aims to improve early detection of mechanical and electrical faults in offshore wind turbines using advanced condition monitoring systems, with work involving analytical modelling, simulations, finite element analysis, and experimental validation. The project addresses a critical gap in current monitoring systems, which struggle with false alarms and poor detection of electrical faults.
