Who are we?
A school of the Institut Mines-Télécom, Télécom Paris is the leading French school for generalist digital engineers. With its excellent teaching and research, Télécom Paris is at the heart of a unique innovation ecosystem based on the transversality of its training, its research departments and its business incubator.
A founding member of the Institut Polytechnique de Paris, Télécom Paris is positioned as an open-air laboratory for all the major technological and societal challenges.
New digital applications require more and more connected objects integrating complex algorithms and having to satisfy a high level of performance and robustness (autonomous vehicle, IoTs, high-speed networks, industry 4.0, smart home, etc). The SSH team responds to these new needs with ambitious projects in collaboration with numerous academic and industrial partners. The team’s research focuses on the architectures of embedded systems and digital circuits under strong constraints aimed at optimizing performance in terms of execution speed, security, reliability, complexity and low power. The validation of the properties to be satisfied is based on mathematical formalism, model simulations and prototype designs based on hardware and software technologies. Télécom Paris has identified a strong need in the areas of Artificial Intelligence/Machine Learning (AI/ML) with applications relying on Internet of Things and embedded systems. The use of artificial intelligence algorithms in embedded systems is a major and strategic use case addressed by SSH. Inferring AI models at the "edge" or end-user level in connected objects provides many benefits that require exploration at all levels: algorithms, architectures, technology, and optimization of computation and memory in resource-constrained systems. The implementation of AI models must also be done without compromising the safety and security of algorithms and data. This research is done in close collaboration with teams competent in circuit design (C2S, LabSoC), embedded software (ACES) and machine learning (S2A) at Télécom Paris.
The SSH team is also characterized by an important teaching activity in the engineering and Masters courses on the theme of embedded systems with a pedagogy marked by practical work and projects. It relies on research activities in order to integrate into its courses the most recent technologies and design methods.
PREFERED SCIENTIFIC EXPERTISE
The candidate will be an early to mid-career PhD-qualified academic looking to develop and establish your research and apply and grow your teaching skills. He/she should ideally have a strong research record that involves design of embedded systems, machine learning (in particular tiny ML), applied signal processing, internet of things, etc.
More precisely, the candidate must have skills in architectures and design methods of embedded systems and circuits based on hardware and software technologies. He/she must master the theory and practice of embedded systems, from algorithm to prototyping using modeling-based validation, FPGA and/or ASIC technologies, processor cores and their software layers. In addition, the candidate must have a very good knowledge of AI algorithms, especially those based on machine learning, and significant experience in their implementation with software and/or hardware technologies. On this last point, it would be desirable to have been confronted with optimization work to find the best adequation between an AI algorithm and an architecture satisfying numerous physical and cost constraints.
Significant experience in publishing in leading journals and conferences is required. The candidate must have the ability to initiate academic and industrial projects and collaborations within IP Paris and with the best national and international teams. Experience in higher education and fluency in written and spoken English are essential.
The candidate with complementary skills in information and communication technology engineering in the following areas is a plus:
Required skills, experience, and knowledge:
Preferred skills, experience, and knowledge:
Other abilities and skills:
Applicants should submit a single PDF file that includes and using the following link:
Contact for further information:
The selection process consists of 4 steps: