Postdoctoral Research Visit F/M Distributed Machine Learning at the Network Edge: Research Position
il y a 2 semaines
Job Context and Requirements
The position is part of the dAIEDGE project, a network of excellence for distributed, trustworthy, efficient, and scalable AI at the Edge, funded by the European Union.
The dAIEDGE Network of Excellence aims to strengthen and support the development of the dynamic European edge AI ecosystem under the umbrella of the European AI Lighthouse and to sustain the advanced research and innovation of distributed AI at the edge as essential digital, enabling, and emerging technology in an extensive range of industrial sectors.
The candidate will work with the NEO Inria team, consisting of Giovanni Neglia, Chuan Xu, and Frédéric Giroire.
Research Mission
The Internet was initially designed to enable computer resources' time-sharing, but it soon became the primary function to deliver content to end users. However, it is now called to play a new key role: to pervasively support machine learning (ML) operation both for model training and prediction serving.
There are two aspects calling for Internet-wide deployment of ML systems. First, data, one key ingredient of ML success, is often generated by users and devices at the edge of the network. The classic ML operation in the cloud requires such data to be collected at a single computing facility where training occurs. Data aggregation can be very costly, or simply impossible because of capacity constraints, privacy issues, or ownership ones. These scenarios call for distributed learning systems, where computation moves, at least in part, to the data. For example, Google's federated learning enables mobile phones, or other devices with limited computing capabilities, to collaboratively learn an ML model while keeping all training data locally. Distributed ML training is already a difficult task in a cluster setting. Indeed, optimization techniques, distributed systems, and ML models are a triad difficult to untangle: e.g., relaxed state consistency across computing nodes increases system throughput but may jeopardize convergence of the optimization algorithm or affect the final solution selected, leading to models with very different generalization capabilities.
Additional challenges arise when training moves to the Internet. First, the system potentially scales up to billions of devices, against at most thousands of GPUs to break ML training records in a cluster. Second, local datasets are highly heterogeneous with very different sizes and feature/label distributions. Third, devices may have very different hardware and connectivity. Fourth, communications are often unreliable (devices can be switched off at any time), slow (latencies are 2 orders of magnitude larger), and expensive for battery-constrained devices. Fifth, privacy concerns are often important and limit the operations that can be performed during training to avoid inadvertently disclosing sensible information. Finally, training is more vulnerable to malicious attacks. For all these reasons, federated learning (as ML training over the Internet is now usually called) has emerged in the last years as a specific research topic—well distinct for example from high-performance computing or cloud computing—at the intersection of machine learning, optimization, distributed systems, and networking.
Research Topics
We are looking for a postdoc candidate who could join our team to work on one or more of the following topics:
- Distributed Inference
- Online Learning Algorithms with Regret Guarantees
- Distributed/Federated Learning
- Machine Learning Privacy
Expected Activities
We expect the postdoc to actively participate to the activities of the EU project dAIEDGE (e.g., attending meetings, coordinating Inria contribution to deliverables).
The postdoc will also have the opportunity to collaborate with PhD students working on the topics listed above.
Required Skills
Candidates must hold a Ph.D. in Applied Mathematics, Computer Science, or a closely related discipline. Candidates must also show evidence of research productivity (e.g., papers, patents, presentations, etc.) at the highest level.
We prefer candidates who have strong mathematical background (on optimization, statistical learning, or privacy) and in general are keen on using mathematics to model real problems and get insights. The candidate should also be knowledgeable on machine learning and have good programming skills. Previous experiences with PyTorch or TensorFlow is a plus.
Benefits
- Subsidized meals
- Partial reimbursement of public transport costs
- Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.)
- Possibility of teleworking and flexible organization of working hours
- Professional equipment available (videoconferencing, loan of computer equipment, etc.)
- Social, cultural, and sports events and activities
- Access to vocational training
- Contribution to mutual insurance (subject to conditions)
Salary
Gross Salary: 2746 € per month
-
Technopole de Sophia Antipolis, France INRIA Temps pleinAbout the Postdoctoral Research PositionThe postdoctoral research position in our team at INRIA is focused on distributed machine learning at the network edge. The successful candidate will work on designing and developing novel machine learning algorithms and systems that can operate efficiently and effectively in distributed edge environments. The position...
-
Technopole de Sophia Antipolis, France INRIA Temps pleinResearch Position Overview We are seeking a highly motivated postdoctoral researcher to join our team at INRIA and work on distributed machine learning at the network edge. The successful candidate will be part of the dAIEDGE project, a network of excellence for distributed, trustworthy, efficient, and scalable AI at the edge, funded by the European Union....
-
Technopole de Sophia Antipolis, France INRIA Temps pleinJob DescriptionWe are seeking a highly motivated postdoctoral researcher to join our team at INRIA to work on distributed machine learning at the network edge. The position is part of the EU-funded project dAIEDGE, which aims to develop distributed, trustworthy, efficient, and scalable AI at the Edge.The successful candidate will work with our team to...
-
Technopole de Sophia Antipolis, France INRIA Temps pleinJob DescriptionWe are seeking a highly motivated postdoctoral researcher to join our team at INRIA to work on distributed machine learning at the network edge. The successful candidate will have a strong background in machine learning, optimization, and distributed systems, and will be responsible for conducting research and developing new algorithms and...
-
Technopole de Sophia Antipolis, France INRIA Temps pleinJob DescriptionWe are seeking a highly motivated postdoctoral researcher to join our team at INRIA to work on distributed machine learning at the network edge. The successful candidate will have a strong background in machine learning, optimization, and statistical learning, and will be able to apply mathematical techniques to model real-world...
-
Technopole de Sophia Antipolis, France INRIA Temps pleinJob DescriptionWe are seeking a highly motivated postdoctoral researcher to join our team at INRIA and work on distributed machine learning at the network edge. The successful candidate will have a strong background in machine learning, optimization, and statistical learning, and will be able to contribute to the development of new algorithms and techniques...
-
Technopole de Sophia Antipolis, France INRIA Temps pleinJob DescriptionWe are seeking a highly motivated postdoctoral researcher to join our team at INRIA to work on distributed machine learning at the network edge. The successful candidate will have a strong background in machine learning, optimization, and statistical learning, and will be able to apply mathematical techniques to model real-world problems.The...
-
Technopole de Sophia Antipolis, France INRIA Temps pleinJob DescriptionWe are seeking a highly motivated postdoctoral researcher to join our team at INRIA to work on distributed machine learning at the network edge. The successful candidate will be part of the dAIEDGE project, a European Union-funded initiative to develop distributed, trustworthy, efficient, and scalable AI at the edge.Key ResponsibilitiesConduct...
-
Technopole de Sophia Antipolis, France INRIA Temps pleinJob DescriptionWe are seeking a highly motivated postdoctoral researcher to join our team at INRIA to work on distributed machine learning at the network edge. The successful candidate will have a strong background in machine learning, optimization, and distributed systems, and will be responsible for conducting research and developing new algorithms and...
-
Technopole de Sophia Antipolis, France INRIA Temps pleinJob DescriptionWe are seeking a highly skilled postdoctoral researcher to join our team at INRIA, working on distributed machine learning and edge AI. The successful candidate will be part of a dynamic team focused on developing innovative solutions for edge AI and federated learning.Key ResponsibilitiesConduct research in distributed machine learning and...
-
Technopole de Sophia Antipolis, France INRIA Temps pleinContext and ChallengesWe are seeking a postdoctoral researcher to join our team at INRIA to work on distributed machine learning at the edge. The successful candidate will be part of a research project focused on enhancing the European edge AI ecosystem.Background and MotivationsThe Internet was initially designed for time-sharing, but it has evolved to...
-
Senior Researcher in Distributed Machine Learning at INRIA
il y a 4 jours
Technopole de Sophia Antipolis, France INRIA Temps pleinAbout the PositionContext and RequirementsThe INRIA research center is seeking a highly skilled postdoctoral researcher to join our team and work on the dAIEDGE project, a European Union-funded network of excellence for distributed, trustworthy, efficient, and scalable AI at the edge.The successful candidate will have the opportunity to collaborate with our...
-
Technopole de Sophia Antipolis, France INRIA Temps pleinContext and Benefits of the PositionThe Postdoctoral Research Visit is part of the LearnNet project, a collaboration between Inria and Nokia Bell Labs. The successful candidate will contribute to the development of inference delivery networks, a novel approach to machine learning inference tasks.Research ObjectivesThe research goals of this position are to...
-
Postdoctoral Researcher
Il y a 2 mois
Technopole de Sophia Antipolis, France INRIA Temps pleinAbout the PositionWe are seeking a highly skilled Postdoctoral Researcher to join our team at INRIA, focusing on Cooperative Inference Strategies. This position is part of a research project that aims to develop novel inference delivery networks for machine learning applications.Research GoalsThe successful candidate will work on designing and implementing...
-
Postdoctoral Research Visit F/M Cooperative Inference Strategies
il y a 2 semaines
Technopole de Sophia Antipolis, France INRIA Temps pleinResearch Position in Cooperative Inference StrategiesThis postdoctoral research visit is part of the Inria-Nokia Bell Labs challenge LearnNet (Learning Networks). The researcher will work on inference delivery strategies in networks of computing nodes that coordinate to satisfy machine learning inference requests.Research GoalThe goal of this research is to...
-
Post-doctoral Research Visit F/m Distributed
Il y a 5 mois
Sophia Antipolis, France Inria Temps pleinLe descriptif de l’offre ci-dessous est en Anglais_ **Type de contrat **:CDD**Niveau de diplôme exigé **:Thèse ou équivalent**Fonction **:Post-DoctorantA propos du centre ou de la direction fonctionnelle The Inria centre at Université Côte d'Azur includes 37 research teams and 8 support services. The centre's staff (about 500 people) is made up of...
-
Postdoctoral Research Visit F/M Cooperative Inference Strategies
il y a 2 semaines
Technopole de Sophia Antipolis, France INRIA Temps pleinResearch PositionThis postdoctoral research visit is part of the Inria-Nokia Bell Labs LearnNet challenge, focusing on cooperative inference strategies in machine learning. The successful candidate will work with a team of researchers to develop novel inference delivery networks, integrating machine learning models with different computational and memory...
-
Postdoctoral Researcher in Cooperative Inference Strategies
il y a 3 semaines
Technopole de Sophia Antipolis, France INRIA Temps pleinJob DescriptionContext and OpportunitiesThis postdoctoral research position is part of the Inria-Nokia Bell Labs collaboration on LearnNet (Learning Networks). The successful candidate will work with a team of researchers from Inria and Nokia to develop novel inference delivery strategies for machine learning models.Research GoalsThe postdoctoral researcher...
-
Machine Learning Engineer
il y a 1 mois
Technopole de Sophia Antipolis, France INRIA Temps pleinJob DescriptionContext and Key ResponsibilitiesThis postdoctoral research position is part of the Inria-Nokia Bell Labs collaboration, LearnNet (Learning Networks). The successful candidate will work on developing inference delivery strategies for machine learning models in Inference Delivery Networks (IDNs).Research ObjectivesThe primary goal of this...
-
Technopole de Sophia Antipolis, France INRIA Temps pleinProject OverviewAs a postdoctoral research visitor in our team, you will work on developing novel federated learning algorithms to address the challenges of privacy and security in distributed machine learning systems. Our goal is to create a secure and efficient federated learning framework that can be applied in various domains, including healthcare,...
