18 PhD positions available in MSCA Doctoral Network
Embedded AI Systems and Applications
About
DN ANT
Embedded Artificial Intelligence (AI) has emerged as a transformative technology with immense potential to revolutionize various domains, spanning from robotics and healthcare to environmental monitoring and the Internet of Things. This Doctoral Network (DN) project ANT aims to train a network of 18 excellent Doctoral Candidates (DCs) by addressing the fundamental challenges of Embedded AI and accelerating the development of Embedded AI systems and applications through an innovative and interdisciplinary research and training program.
MSCA DN ANT Consortium
Beneficiaries
Associated Partners
Available positions
- DC1: Sparse on-device training
- DC2: Adaptive sensor- and context-aware learning
- DC3: Battery-free Embedded AI
- DC4: Split learning over distributed heterogeneous devices
- DC5: Task-Agnostic Multimodal Foundation Models on Edge Devices
- DC6: Efficient and realistic over-the-air-computing
- DC7: Zero-power network pervasive intelligence
- DC8: Secure explainable Embedded AI
- DC9: Diagnosing Embedded AI Models
- DC10: Embedded IoT Intelligence for Battery-free Swimming Milli-robots
- DC11: Embedded active inference for autonomous robot manipulation
- DC12: Split Learning across underwater and surface devices
- DC13: 1-Bit Foundation Models for Smart Farming
- DC14: Distributed inferencing on zero/low power embedded devices in smart farming
- DC15: Continual on-tiny-device learning for dynamic environments
- DC16: Networked scalable learning
- DC17: Privacy in Embedded AI
- DC18: Exploring uncertainty quantification of on-device learning for health
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