Secure and Agile Hardware/Software Implementation of new Post-Quantum Cryptography Digital Signature Algorithms
Cryptography plays a fundamental role in securing modern communication systems by ensuring confidentiality, integrity, and authenticity. Public-key cryptography, in particular, has become indispensable for secure data exchange and authentication processes. However, the advent of quantum computing poses an existential threat to many of the traditional public-key cryptographic algorithms, such as RSA, DSA, and ECC, which rely on problems like integer factorization and discrete logarithms that quantum computers can solve efficiently. Recognizing this imminent challenge, the National Institute of Standards and Technology (NIST) initiated in 2016 a global effort to develop and standardize Post-Quantum Cryptography (PQC). After three rigorous rounds of evaluation, NIST announced its first set of standardized algorithms in 2022. While these algorithms represent significant progress, NIST has expressed an explicit need for additional digital signature schemes that leverage alternative security assumptions, emphasizing the importance of schemes that offer shorter signatures and faster verification times to enhance practical applicability in resource-constrained environments. Building on this foundation, NIST opened a new competition to identify additional general-purpose signature schemes. The second-round candidates, announced in October 2024, reflect a diverse array of cryptographic families.
This research focuses on the critical intersection of post-quantum digital signature algorithms and hardware implementations. As the cryptographic community moves toward adoption, the challenge lies not only in selecting robust algorithms but also in deploying them efficiently in real-world systems. Hardware implementations, in particular, must address stringent requirements for performance, power consumption, and security, while also providing the flexibility to adapt to multiple algorithms—both those standardized and those still under evaluation. Such agility is essential to future-proof systems against the uncertainty inherent in cryptographic transitions. The primary objective of this PhD research is to design and develop hardware-agile implementations for post-quantum digital signature algorithms. The focus will be on supporting multiple algorithms within a unified hardware framework, enabling seamless adaptability to the diverse needs of evolving cryptographic standards. This involves an in-depth study of the leading candidates from NIST’s fourth-round competition, as well as those already standardized, to understand their unique computational requirements and security properties. Special attention will be given to designing modular architectures that can support different signatures, ensuring versatility and extensibility. The proposed research will also explore optimizations for resource efficiency, balancing trade-offs between performance, power consumption, and area utilization. Additionally, resilience against physical attacks (side-channel attacks and fault injection attacks) will be a key consideration in the design process. This PhD project will be conducted within the PEPR PQ-TLS project in collaboration with the TIMA laboratory (Grenoble), the Agence nationale de la sécurité des systèmes d’information (ANSSI) and INRIA.
Distributed Passive Radar
Our objective is to detect and locate drones entering an urban area to be protected by observing the signals emitted by cellular stations. Studies have shown that it is possible to locate a drone if it is close to the listening system and the cellular station (i.e. the base station). When the situation is more complex (i.e. there is no direct path between the cellular station and the radar or in the presence of several transmitting cellular stations causing a high level of interference), a single listening system called passive radar cannot correctly detect and locate the drone. To overcome these difficult conditions, we wish to distribute or deploy in the area to be protected a set of low-complexity passive radars which optimally exploit the signals emitted by these cellular stations. A distribution and deployment strategy for passive radars must then be considered by taking into account the positions of the transmitting cellular stations. The possibility of exchanging information between passive radars must also be considered in order to better manage interference linked to cellular stations.
For high-performance, safe, and long-lasting batteries: understanding the role of an additive in liquid electrolytes
The trade-off between performance, aging, and safety remains a major challenge for Li-ion batteries [1]. Indeed, the incorporation of certain additives into the 3rd-generation electrolyte aims to delay or reduce the consequences of thermal runaway, thus reducing the risk of fire or explosion. However, this approach can have negative effects on other key parameters, such as ionic conductivity [2,3]. Therefore, this thesis proposes to study the coupled effects of these additives in order to better understand and potentially predict their impact on each of these indicators.
At the beginning of this work, an additive will be selected to study its role in an NMC 811/Gr-Si chemistry and a 3rd-generation liquid electrolyte, in terms of performance, long-term stability, and safety. The additive will be chosen based on the state of the art and post-mortem analysis of commercial cells representative of the current market. In parallel, new commercial cells of a few Ah will be used. These will be equipped with a reference electrode, internal temperature measurement, and ionic conductivity monitoring. The cells will then be activated with the selected electrolyte at different additive concentrations. Electrochemical performance, along with chemical and morphological characterization of the materials present, will be studied. Key safety parameters (thermal stability, release of reducing gases, O2, released energy, flammability of the electrolyte) for these new cells will be measured at different additive concentrations. The internal instrumentation, including the reference electrode, will also be used innovatively to study the onset of thermal runaway under these conditions.
A full aging campaign will be conducted over a maximum period of one year. At regular intervals, a sample of cells will be studied to characterize the impact of aging on chemical, electrochemical, and morphological changes, as well as on key safety parameters. The most important mechanisms, along with simplified laws governing safety as a function of additive quantity and aging, will be proposed.
[1] Batteries Open Access Volume 9, Issue 8, August 2023, Article number 427
[2] Journal of Energy Storage 72 (2023) 108493
[3] Energy Storage Materials 65 (2024) 10313
Software support for sparse computation
The performance of computers has become limited by data movement in the fields of AI, HPC and embedded computing. Hardware accelerators do exist to handle data movement in an energy-efficient way, but there is no programming language that allows them to be implemented in the code supporting the calculations.
It's up to the programmer to explicitly configure DMAs and use function calls for data transfers and do program analysis to identify memory bottleneck
In addition, compilers were designed in the 80s, when memories worked at the same frequency as computing cores.
The aim of this thesis will be to integrate into a compiler the ability to perform optimizations based on data transfers.
Numerical optimisation of internal safety devices of batterry cells depending on chemistry
Thermal runaway (TR) of a battery pack's elementary accumulator is a key factor that can lead to various safety issues, such as fires or explosions, involving both property and people. Several safety devices can prevent and/or mitigate the consequences of thermal runaway, including the PTC (Positive Temperature Coefficient) to limit short-circuit current, the CID (Current Interrupt Device) to disconnect the external electrical terminals from the internal active elements, and the Safety Vent for cell depressurization. Internal gas pressure is the main triggering factor. However, since the gas quantity strongly depends on the chemistry involved, these safety devices should be optimized for future battery generations.
In this PhD thesis, we will develop a methodology for sizing these safety devices through numerical simulations, incorporating all characterizations from the material scale to abusive cell testing. This research will therefore focus on both numerical and experimental aspects in parallel, in collaboration with other laboratories in our department
EM Signature Modeling in Multi-path Scenario for Object Recognition and Semantic Radio SLAM
Context:
The vision for future communication networks includes providing highly accurate positioning and localization in both indoor and outdoor environments, alongside communication services (JCAS). With the widespread adoption of radar technologies, the concept of Simultaneous Localization and Mapping (SLAM) has recently been adapted for radiofrequency applications. Initial proof-of-concept demonstrations have been conducted in indoor environments, producing 2D maps based on mmWave/THz monostatic backscattered signals. These measurements enable the development of complex state models that detail the precise location, size, and orientation of target objects, as well as their electromagnetic properties and material composition.
Beyond simply reproducing maps, incorporating object recognition and positioning within the environment adds a semantic layer to these applications. While semantic SLAM has been explored with video-based technologies, its application to radiofrequency is still an emerging area of research. This approach requires precise electromagnetic models of object signatures and their interactions with the surrounding environment. Recent studies have developed iterative physical optics and equivalent current-based models to simulate the free-space multistatic signature of nearby objects.
PhD Thesis:
The objective of this thesis is to study and model object backscattering in a multi-path scenario for precise imaging and object recognition (including material properties). The work will involve developing a mathematical model for the backscattering of sensed objects in the environment, applying it to 3D SLAM, and achieving object recognition/classification. The model should capture both near- and far-field effects while accounting for the impact of the antenna on the overall radio channel. The study will support the joint design of antenna systems and the associated processing techniques (e.g., filtering and imaging) required for the application.
The PhD student will be hosted in the Antenna and Propagation Laboratory at CEA LETI in Grenoble, France. The research will be conducted in partnership with the University of Bologna.
Application:
The position is open to outstanding students with a Master of Science degree, “école d’ingénieur” diploma, or equivalent. The student should have a specialization in telecommunications, microwaves, and/or signal processing. The application must include a CV, cover letter, and academic transcripts for the last two years of study.
Advanced RF circuit design in a system and technology co-optimization approach
This thesis addresses the two major challenges facing Europe today in terms of integrating the communication systems of the future. The aim is to design RF integrated circuits using 22nm FDSOI technology in the frequency bands dedicated to 6G, which will not only increase data rates but also reduce the carbon footprint of telecoms networks. At the same time, it is essential to consider the evolution of silicon technologies that could improve the energy efficiency and effectiveness of these circuits. This work will be carried out with an eye to the design methodology of radio frequency systems.
Within the framework of the thesis, the objective will be broken down into three phases. Firstly, simulation tools will be developed to predict the performance of Leti's future 10nm FDSOI technology. The second stage will involve identifying the most relevant architectures available in the literature for the application areas envisaged for the technology. A link with upstream telecoms projects will be systematically established to ensure that the candidate understands the systems' challenges.
Finally, in order to validate the concepts developed, the design of an LNA and a VCO as part of an ongoing project in the laboratory will be proposed.
The candidate will join a large team that works on new communication systems and addresses aspects of architectural study, modeling and design of integrated circuits. The candidate must have serious skills in the design of integrated circuits and radio frequency systems as well as good ability to work in a team.
Scalable thermodynamic computing architectures
Large-scale optimisation problems are increasingly prevalent in industries such as finance, materials development, logistics and artificial intelligence. These algorithms are typically realised on hardware solutions comprising clusters of CPUs and GPUs. However, at scale, this can quickly translate into latencies, energies and financial costs that are not sustainable. Thermodynamic computing is a new computing paradigm in which analogue components are coupled together in a physical network. It promises extremely efficient implementations of algorithms such as simulated annealing, stochastic gradient descent and Markov chain Monte Carlo using the intrinsic physics of the system. However, no clear vision of how a realistic programmable and scalable thermodynamic computer exists. It is this ambitious challenge that will be addressed in this PhD topic. Aspects ranging from the development computing macroblocks, their partitioning and interfacing to a digital system to the adaptation and compilation of algorithms to thermodynamic hardware may be considered. Particular emphasis will be put on understanding the trade-offs required to maximise the scalability and programmability of thermodynamic computers on large-scale optimisation benchmarks and their comparison to implementations on conventional digital hardware.
In situ 3D visualization and modeling of grain growth during solidification of 316L steel in welding and additive manufacturing processes
CEA is currently carrying out R&D studies to assess the potential of Additive Manufacturing (AM) processes using wire deposition (WAAM and WLAM) for 316L steel, a material used in the manufacture of a large number of components. These processes are similar to the welding techniques currently used in the manufacture and repair of parts for the nuclear industry. Microstructures with a strong crystallographic texture are often obtained after welding or additive manufacturing, leading to highly anisotropic mechanical behaviors, and the prediction of these microstructures is also a key element in ensuring the reliability of non-destructive testing of parts manufactured in this way.
The aim of the thesis, which will be based on a coupled experimental/simulation approach, is to gain a better understanding of the main physical phenomena involved in solidification, in particular grain growth.
To this end, an original approach to characterizing these phenomena will be conducted on the basis of an innovative instrumented test, with the aim of obtaining a high-resolution quasi-3D view of the molten zone during solidification. The results of the experimental approach will enrich the physical models of solidification, already implemented in a 3D CA-FE (Cellular Automaton-Finite Element) model, combining a Cellular Automata (CA) approach and thermal or multiphysics modeling (FE) of the molten bath, to simulate the solidification microstructures resulting from additive manufacturing and welding processes.