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Postdoctoral Researcher in AI Model Optimization
Il y a 3 mois
Context and Advantages of the Position
This postdoctoral opportunity is supported by the collaborative initiative between Inria and Nokia Bell Labs, focusing on Learning Networks.
Assigned Responsibilities
Key Tasks:
In this role, the researcher will investigate the complexities surrounding the placement of AI models within Inference Delivery Networks (IDNs). This presents a significant optimization challenge, requiring a careful balance between model performance, inference speed, and resource allocation, while also accommodating the inherent variability of the network, such as fluctuations in user demand or changes in available computational and communication resources.
Additional metrics, including energy efficiency, will be integrated into the optimization objectives and networking constraints, particularly in systems exhibiting inelastic characteristics. The researcher will employ multi-objective optimization strategies, such as identifying Pareto optimal solutions, alongside transfer learning methods to adapt models across nodes with varying levels of expertise and resource capacity. Online learning techniques will also be utilized to ensure model placements are robust against adversarial conditions.
Unlike previous studies, this research will explore the feasibility of distributing models across multiple nodes. The focus will be on evaluating specific model partitioning strategies, both with and without the inclusion of bottlenecks, assessing their impact on performance indicators such as inference latency and network utilization. Various methodologies will be examined to estimate the quality of inference in real-time.
This assessment may extend to scenarios characterized by significant node heterogeneity, such as those encountered in embedded Edge AI applications or even in TinyML contexts, where resource constraints may be drastically lower, yet the number of devices could be substantially higher.
Collaboration:
The selected candidate will be based at Inria Saclay and will work under the guidance of experts from Tribe (INRIA), Neo (INRIA), and AIRL (Nokia).
Main Activities
- Conduct comprehensive literature reviews and synthesize findings.
- Engage in pioneering research at the intersection of networking and artificial intelligence.
- Develop innovative methodologies and technical solutions for AI model placement.
- Prepare and submit research papers to leading conferences and journals in the fields of networking, AI, and computer science.
- Share research outcomes through presentations at academic conferences, seminars, and workshops.
Required Skills
- Strong understanding of networking principles, protocols, and architectures.
- Proficiency in programming languages relevant to AI and networking research.
- Experience with pertinent libraries and frameworks is advantageous.
- Capability to design and implement algorithms for complex problem-solving.
- Familiarity with optimization techniques.
- Excellent written and verbal communication skills for articulating research findings and collaborating with peers.
- Adeptness in working collaboratively within a research team, engaging with colleagues from diverse backgrounds, and fostering positive group dynamics.
Benefits
- Subsidized meals.
- Partial reimbursement for public transportation expenses.
- Generous leave policy: 7 weeks of annual leave plus additional days off.
- Flexible working hours and the possibility of remote work.
- Access to professional equipment and resources.
- Participation in social, cultural, and sports events.
- Opportunities for vocational training.
- Comprehensive social security coverage.
