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Akin Delibasi

3 months ago

Postdoctoral Researcher in Implicit Neural Networks, Lyapunov Stability, and Data-Driven Control Inria Saclay in France

Degree Level

Postdoc

Field of study

Computer Science

Funding

Fixed-term postdoctoral position for 2 years with a gross salary of €2,788 per month. Benefits include subsidized meals, partial reimbursement of public transport costs, 7 weeks of annual leave plus 10 extra RTT days, teleworking/flexible hours, professional equipment, social/cultural/sports activities, vocational training, and social security coverage.

Deadline

Oct 1, 2026

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Country

France

University

CEA Saclay

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Keywords

Computer Science
Machine Learning
Electrical Engineering
Mathematics
Optimisation
Robotics
Lyapunov Function

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About this position

Postdoctoral researcher opportunity in implicit neural networks, Lyapunov stability, data-driven control, and machine learning at the interface of artificial intelligence and control systems.

The position is a collaboration between Inria Saclay DISCO (CentraleSupélec / Paris-Saclay ecosystem) and University College London through the UCL-Inria Joint Centre. The research focuses on whether implicit neural networks can provide stronger stability and safety certificates than standard feedforward architectures, with particular attention to the expressivity of neural parameterizations of Lyapunov functions, smooth vs. non-smooth activations, neural network verification, and training strategies for implicit models.

The postdoctoral researcher will spend 12 months in Palaiseau, France, and 12 months in London, UK. The role is supervised by Prof. Giorgio Valmorbida and Prof. Akin Delibasi. The project includes developing theoretical and computational methods for control Lyapunov functions, optimization-based control design, and comparing implicit and feedforward neural networks under equivalent parameterization constraints.

Eligibility highlights: PhD or equivalent in control theory, artificial intelligence, or a closely related field; strong background in nonlinear control, Lyapunov analysis, and optimization; advanced programming in Python and MATLAB; fluent English; French is an asset; strong publication record expected.

Funding and conditions: fixed-term 2-year contract with a gross salary of €2,788/month. Benefits include subsidized meals, transport reimbursement, leave allowances, teleworking options, equipment, training, and social security coverage.

Deadline: 2026-10-01. Start date: 2026-11-02.

Apply via the official Inria job portal. The post also provides a research proposal download link and notes that applications submitted through other channels may not be processed.

Funding details

Fixed-term postdoctoral position for 2 years with a gross salary of €2,788 per month. Benefits include subsidized meals, partial reimbursement of public transport costs, 7 weeks of annual leave plus 10 extra RTT days, teleworking/flexible hours, professional equipment, social/cultural/sports activities, vocational training, and social security coverage.

What's required

Applicants must hold a PhD or equivalent in control theory, artificial intelligence, or a closely related discipline. Required expertise includes artificial intelligence methods such as machine learning, reinforcement learning, and data-driven modeling, as well as nonlinear control systems. A solid theoretical background in Lyapunov stability analysis and optimization-based control design is required. Strong programming skills in Python and MATLAB are expected. Fluency in English is required; French proficiency is considered an asset. A significant publication record in leading international journals and conferences is required, with emphasis on originality, scientific innovation, mathematical rigor, and clarity of presentation.

How to apply

Apply online through the Inria website using the official job portal. The post notes that applications sent through other channels are not guaranteed to be processed. A research proposal is available via the provided file link, and the job page contains the full application details.

More information can be found here

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