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Grégoire Danoy

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Postdoc in Swarm Intelligence and Reinforcement Learning for Autonomous Robotics University of Luxembourg in Luxembourg

Degree Level

Postdoc

Field of study

Computer Science

Funding

Available

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Country

Luxembourg

University

University of Luxembourg

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Keywords

Computer Science
Mathematics
Cybersecurity
Parallel Computing
Python Programming
Reinforcement Learning
Swarm Intelligence
Optimisation
Robotics
Metaheuristic
Embedded System
Machine learning

About this position

The University of Luxembourg, a leading international research university, offers a postdoctoral position in Swarm Intelligence and Reinforcement Learning for Autonomous Robotics. The role is based at the Interdisciplinary Centre for Security, Reliability and Trust (SnT), specifically within the Parallel Computing and Optimisation Group (PCOG) led by Prof. Grégoire Danoy. The PCOG group specializes in parallel computing, search and optimization techniques, and provides robust solutions to large-scale combinatorial problems.

This postdoctoral opportunity is part of the FEderated droNe Countering system (FENCE) project, a collaboration between the University of Luxembourg and Luxembourg Tech School. The project aims to develop a unique swarm-based counter-UAS approach, enabling autonomous generation and continuous adaptation of protective swarm behaviors. The successful candidate will lead research in Swarm Intelligence and Machine Learning, focusing on counter drone swarm formation and defense. Responsibilities include designing and conducting experiments in both simulation environments and real-world deployments using nano-drones at the University's SwarmLab, disseminating research outcomes through top-tier publications, contributing to research proposal writing, and mentoring PhD students and assistants.

Applicants must have a PhD in a relevant discipline (computer science, applied mathematics, operations research), strong expertise in exact and/or approximated methods, meta-heuristics, and/or machine learning, proven experience in research proposal writing and project management, and solid software development skills in Python (C/C++ is a plus). Fluency in English, commitment, creativity, and teamwork skills are essential. Experience in embedded systems, robotics, or cybersecurity is desirable. Due to project constraints, only applicants from EU EEA/EFTA countries, NATO Allied nations, or NATO Indo-Pacific Partners (Australia, Japan, Republic of South Korea, New Zealand) are eligible.

The University of Luxembourg offers a modern, dynamic, and international environment with high-quality equipment and infrastructure. The postdoctoral contract is for 24 months, with a yearly gross salary of EUR 85,176. The institution promotes an inclusive culture and encourages applications from individuals of all backgrounds.

To apply, candidates should submit their application online via the University of Luxembourg HR system, including a CV, cover letter, PhD diploma or expected defense date, transcript of university-level courses, and a list of publications. Early applications are encouraged as review begins upon receipt. Applications by email will not be considered.

Funding details

Available

What's required

Applicants must hold a PhD in a relevant discipline such as computer science, applied mathematics, or operations research. Strong expertise in exact and/or approximated methods, meta-heuristics, and/or machine learning is required. Proven experience in writing successful research proposals and research project management or coordination is expected. Solid software development skills in Python are essential; C/C++ is a plus. Fluency in English is mandatory. Commitment, creativity, and teamwork skills are required. Experience in embedded systems, robotics, or cybersecurity is desirable. Only applicants from EU EEA/EFTA countries, NATO Allied nations, or NATO Indo-Pacific Partners (Australia, Japan, Republic of South Korea, New Zealand) will be considered.

How to apply

Submit your application online through the University of Luxembourg HR system. Include your CV, cover letter detailing motivation and alignment with the project, PhD diploma or expected defense date, transcript of university-level courses, and list of publications. Early applications are encouraged as review begins upon receipt. Applications by email will not be considered.

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