Assistant/Associate Professor in Embedded & Distributed AI – Palaiseau, France | Academic Salary Insights

📍 Location: eu

🏷 Type: Contract

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Job Overview

This position at Télécom Paris within the Autonomous Critical Embedded Systems (ACES) team targets a research-active academic specializing in embedded AI, distributed systems, and critical system design. The role sits at the intersection of machine learning, robotics, and formal verification, focusing on constrained environments such as IoT devices, autonomous vehicles, and edge computing infrastructures. The ideal candidate is a strong researcher with teaching capabilities, capable of advancing both theoretical and applied AI systems while contributing to France’s leading digital engineering ecosystem within Institut Polytechnique de Paris.

📅 Job Timeline & Status

This is an actively hiring academic role with a clearly defined deadline, indicating a structured selection cycle rather than rolling recruitment. Given the international scope and research intensity, applicants should apply early due to expected high competition from EU and global AI researchers. The presence of a fixed closing date suggests a committee-based evaluation process where early preparation significantly improves interview chances.

🌍 Work Eligibility & Location

This is a HYBRID academic position based in Palaiseau, France. International candidates are generally welcomed within French higher education institutions, especially at Institut Polytechnique de Paris, though formal visa conditions are not explicitly detailed in the posting.

💰 Salary Intelligence

While no official compensation is provided, French assistant/associate professor roles in elite institutions typically follow national academic grids. Total compensation may increase with grants, research funding, and institutional bonuses. Relative to industry AI roles, base pay is moderate, but the role offers strong research autonomy and long-term academic positioning.

📊 Role Breakdown

This position requires deep engagement in embedded AI systems where computational constraints (memory, latency, energy) shape algorithm design. Approximately 40% of effort focuses on research innovation, 30% on teaching responsibilities, and 30% on institutional collaboration and partnerships. The candidate will design optimization strategies such as model pruning, quantization, and neural architecture search (NAS) for edge deployment. Another key pillar involves distributed multi-agent systems, especially for robotics and autonomous systems requiring coordination under uncertainty.

A significant focus is placed on formal verification techniques ensuring safety, robustness, and cybersecurity compliance in AI systems. The role also extends to integrating lightweight foundation models such as LLMs and vision-language-action (VLA) systems into embedded platforms. Research outcomes are expected to influence both academic publications and industrial collaborations, particularly in robotics, IoT, and autonomous mobility systems. Candidates must demonstrate strong ability to bridge theory and system-level implementation in constrained environments.

🧩 Required Skills & Fit

📈 Difficulty & Competitiveness

This is a highly competitive academic appointment requiring strong publication history and demonstrable research leadership in embedded or distributed AI. Candidates with interdisciplinary expertise spanning AI systems and formal methods will have a significant advantage.

🚀 Career Impact

This role provides strong career acceleration in academic AI research, particularly in safety-critical systems and edge intelligence. It is a gateway into high-impact European research networks and collaborative industrial partnerships.

📋 Key Responsibilities

The selected professor will develop and lead research in embedded AI architectures, focusing on efficiency, robustness, and scalability. Core responsibilities include designing compressed neural models, advancing distributed learning frameworks, and ensuring system reliability through formal verification methods. Teaching responsibilities span undergraduate and graduate courses in AI, embedded systems, and distributed computing.

Additionally, the role involves building research collaborations with industry and academic partners, supervising PhD candidates, and contributing to funded projects within the Institut Polytechnique de Paris ecosystem. Integration of edge AI systems, multi-agent robotics, and lightweight foundation models into real-world systems is a key research direction.

🎯 Application Strategy

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🧠 Fit & Positioning Analysis

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📅 Application Signals

This role shows high urgency due to a fixed deadline of July 10, 2026. Academic competition is expected to be strong, particularly from European and international AI researchers specializing in embedded systems. Response times are likely moderate (3–6 weeks post-deadline), reflecting committee-based evaluation cycles.

Given the high competition and structured review process, candidates should apply early and ensure strong research documentation. Interview stages are expected to move quickly once shortlisted, especially for candidates with aligned publications in edge AI, distributed systems, or formal verification.

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✅ Job Source & Verification

This listing originates from Institut Mines-Télécom / Télécom Paris official recruitment portal, which is a highly credible academic hiring source within France’s public higher education system. The information was last verified on June 17, 2026. The posting is considered reliable and authoritative, reflecting a formal institutional hiring process with structured evaluation criteria.