The recruited student will investigate the photophysical mechanisms of reversibly photoswitchable fluorescent proteins (RSFPs) employing solution NMR spectroscopy coupled with in-situ illumination and variable oxygen pressure. RSFPs are capable to switch between a fluorescent on-state and a nonfluorescent off-state under specific light illumination, and have fostered many types of imaging applications including super-resolution methods. Multidimensional NMR spectroscopy is a particularly powerful atomic resolution technique providing detailed information on conformational protein dynamics, as well as the local chemistry (protonation states, H-bonding interactions, …) involved in the photophysics of the chomophore within the protein scaffold. In the proposed PhD project, we intend to further improve our NMR in-situ illumination device by adding capabilities such as additional wavelengths of emitting light sources, fluorescence detection, and oxygen pressure control. This will allow to directly correlate the conformational dynamics of various states with their photophysical properties, as well as the effect of oxygen on triplet state formation and photobleaching. We will apply this NMR methodology to several green and red model RSFPs, as well as FAST systems. The goal will be to contribute fundamental knowledge of these fluorescent markers and to design improved variants.

Understanding reversibly switchable red fluorescent proteins

Fluorescence imaging is essential to unlocking the secrets of life and has benefited greatly from the discovery of fluorescent proteins (FPs). Reversibly switchable fluorescent proteins (RSFPs, are capable of switching from a fluorescent "on-state" to a non-fluorescent "off-state" upon specific illumination, and have fostered many imaging applications, including some super-resolution methods. However, RSFPs are still imperfect: for example, their brightness is limited, their switching kinetics is dependent on environmental conditions, their resistance to irreversible photobleaching is insufficient. In particular, whereas green RSFPs are performing relatively well, red RSFPs have been lagging behind. The switching performances of green and red RSFPs are linked with their intrinsic or light-activated protein-dynamics properties and can be studied by combining structural biology approaches, such as kinetic X-ray crystallography, with optical spectroscopy and fluorescence imaging (doi: 10.1038/s41592-019-0462-3). In the proposed PhD project, those techniques will be used to better understand red RSFPs and facilitate their rational engineering towards brighter and more photo-resistant variants. The recruited student will work in close collaboration with another PhD student to be hired, who will approach the same questions by employing NMR.

Candidates should have a strong interest to work at the interface between physics, chemistry and biology. Knowledge of advanced fluorescence microscopy and/or X-ray crystallography is required. Preliminary experience in image analysis, biochemistry, cell biology and/or molecular biology will be appreciated.

Deciphering the photoactivation mechanism of the orange carotenoid protein by time-resolved serial femtosecond crystallography

The Orange Carotenoid Protein (OCP) is a photoactive protein involved in photoprotection of Cyanobacteria. Recently, a photoactivation mechanism was proposed for OCP, in which the initially excited S2 state yields multiple ps-lived excited states (ICT, S1, S*), but structural evidence is missing. Importantly, only one of these leads to the biologically active OCP-red state on the second timescale. We propose to conduct an ultra-fast time-resolved crystallography experiment at an X-ray free electron laser (XFEL) on OCP to accurately characterize the structures of the short-lived photo-intermediates on the femtosecond to millisecond timescale. In parallel, we will use the new time-resolved crystallography beamline of the ESRF to determine the structures of the later intermediates forming on the millisecond to second timescale. By allowing to visualize protein conformational changes upon photoactivation from the photochemical (hundreds of femtoseconds) to the photobiological timescales (seconds), our integrated structural biology project will allow to (i) test mechanistic hypotheses, (ii) pave the way to a detailed understanding the photophysical properties of OCP, and (iii) open avenues towards its exploitation as an optogenetic component or a regulator of light-uptake in biomimetic photosynthetic systems.

Biosynthesis and functional evaluation of novel antimicrobial peptides from mammalian gut microbiomes

The WHO has identified antibiotic resistance as one of the major threats to human health. According to predictions, the number of deaths related to antibiotic resistance is estimated at 10 million a year by 2050. This situation is prompting scientists to find new molecules, ideally natural ones, whose structures and mode of action differ from those of conventional antibiotics, to overcome the phenomena of resistance. One promising alternative concerns antimicrobial peptides of the RiPPs family (ribosomally synthesized and post-translationally modified peptides) produced by bacteria. Numerous studies show that the intestinal microbiome plays a very important role in the health of the host. Among the mechanisms involved, the production of antimicrobial peptides appears to be of particular importance. Part of our collaborative work aims to identify new antimicrobial peptides from complex biological ecosystems using metagenomic methods. To date, we have identified ten potentially interesting sequences. In this project, we will focus on the biosynthesis as well as the biochemical and structural characterizations of the antimicrobial peptides. An important part of the project will be devoted to the biological activity of these compounds on resistant and multi-resistant pathogens to conventional antibiotics. Moreover, the mode of action and the toxicity of the most effective peptides will be addressed.

Hierarchically conducting polymer coated on 3D ALD/Silicon nanostructures for integrated solid and flexible micro-supercapacitors

The objective of this thesis is to develop and high performance and durable all-solid state flexible micro-supercapacitors (micro-SC). These new solid-state micro-generators will operate over a wide temperature range (-50°C to +120°C) and exhibit exceptional lifetime and performance. The ?-SCs proposed in this thesis project are based on i) the elaboration by CVD growth of electrodes composed of silicon nanowires and nanotrees followed by a nanometric deposition of a dielectric and new electronically conductive polymer, ii) the elaboration and characterization of new copolymers based on n-type EDOTs derivativesiii) the synthesis of polymeric solid electrolytes (ESPs) based on poly(siloxane)s and ionogels iv) performance tests of different electrodes and electrolytes in three-electrode system configuration, v) elaboration of nanocomposites based on EDOT-based electronically conductive polymers and silicon nanowires covered with nanometric layers of alumina and HfO2, and v) assembly and tests of devices in rigid and flexible sandwich type configuration

Reliable In Memory Computing Implementation of stochastic ultra-low-power bio- inspired neural networks

The automated resolution of cognitive tasks primarily relies on learning algorithms applied to neural networks which, when executed on standard CMOS based digital architectures, lead to a power consumption several orders of magnitude larger than what the brain would require. Moreover, Conventional Edge neural network solutions can only provide output predictions, lacking the ability to accurately convey prediction uncertainty due to their deterministic parameters and neuron activations, resulting in overconfident predictions. Being able to model and compute the uncertainty of a given prediction allows the user to make better decisions (e.g. in classification or decision making processes) that can be therefore explained, which is crucial in a variety of applications, such as the safety-critical tasks (e.g., autonomous vehicles, medical diagnosis and treatment, industrial robotics, and financial systems). Probabilistic neural network is a possible solution to deal with uncertainty prediction. In addition, the power consumption can be drastically reduced by using hardware computing systems with architectures inspired by biological or physical models. They are mainly based on nanodevices mimicking the properties of neurons such as the emission of stochastic or synchronous spikes. Numerous theoretical proposals have shown that nanoscale spintronic devices (MTJ) are particularly well adapted. They can be used as stochastic components or as deterministic components.

Deciphering Complex Energy Landscape at Atomic Resolution of Human HSP90 using NMR and AI-Enhanced tools.

HSP90 is a human chaperone involved in the folding of a wide variety of client proteins, including many oncogenic proteins. This complex molecular machinery is known to undergo massive conformational rearrangements throughout its functional cycle. X-ray crystallography and cryoEM have provided high-resolution snapshot structures of this human machinery in complex with cochaperones and client proteins, but have failed to provide the kinetic and time-resolved information needed for a full understanding of its mechanism. We plan to use NMR experiments combined with a new AI-enhanced analysis tool to obtain a detailed picture of the energy landscape of this important drug target. This project will provide structural information on the different excited states of HSP90 and the conformational dynamics between these states. In collaboration with the pharmaceutical industry, we will exploit this new approach to reveal how ligands can modulate the energy landscape and population of different functional states. This information will be particularly useful for the design of new drugs capable of blocking the HSP90 chaperone in a single state, an important step towards the development of more specific and effective drugs.

Study of emerging materials for Threshold Switching Selector for MRAM technology

The objective of this thesis is to explore novel Threshold Switching Selector (TSS) materials for emerging MRAM (Magnetic Random-Access Memory) technologies. A selector serves as a simple two-terminal device, behaving like a switch or a diode that turns on above a certain voltage and stays off otherwise. When combined to a memory element, it prevents sneak current in non-selected memory cells, enabling denser memories. In addition, TSS aims at replacing the selection transistor and at reducing the number of vias to connect with the CMOS, thus saving power and surface area.
To achieve TSS compatible with MRAM, it is critical to develop new selectors materials that match the characteristics of magnetic tunnel junction (MTJ). For example, Ovonic threshold switch (OTS) used with phase change PC-RAM (in production) has a threshold voltage larger than 2V. This voltage is too high for MTJs that must be operated below 1V to avoid degrading the MgO tunnel barrier.

Spintronics-based non-volatile FPGA development for space applications

In microelectronics, we can distinguish between two types of integrated circuit. ASICs (Application Specific Integrated Circuits) dedicated to only one application and FPGAs (Field Programmable Gate Arrays) dedicated to digital electronics, on which we focus in this thesis. The main advantage of FPGAs is that they can be reprogrammed. These circuits are made up of several elementary logic cells, interconnected via a programmable interconnect system. This makes them particularly sensitive to radiation, since a fault in the memory permanently alters the operation of the FPGA. Traditional FPGAs are based on SRAM or Flash memories. The aim of this thesis is to evaluate the use of MRAM as a configuration and interconnect memory for FPGAs, and in particular as a means of improving/simplifying the implementation of standard hardening techniques for space applications, while reducing cost thanks to its density. The work will involve inserting multi-level magnetic components known as magnetic tunnel junctions, and assessing their value. To do this, we'll be using several simulation tools to inject particles present in space at different points in the circuit, and compare the results with a conventional version. In this way, it will be possible to measure the effectiveness of such a hardening process based on magnetic technology.

Topological-superconductor group IV nanomaterials

We are currently embracing the second quantum revolution, where major breakthroughs in solid-state technologies have been achieved by engineering materials with different electrical conductivities (metals, insulators, semiconductors (SEMI)), eventually reaching infinite conductivity in cooled superconductors (SC). This flourishing ecosystem has been enriched by the recent discovery of a new class of materials with remarkable electronic properties - topological (TOP) materials(1) - that is now driving both the theoretical and experimental work in condensed matter physics. Significant advances in understanding fundamental material properties, devising new fabrication processes, and discovering novel material systems are required to fully harvest the potential of solid-state quantum devices. Superconducting spin qubits, gate-tunable spin qubits, and topological qubits systems are commonly fabricated by combining multiple materials with fundamentally different properties - heterogeneous integration - in hybrid SC/SEMI and SC/TOP junctions. This is a significant challenge in material science since any structural defects and roughness at the interface between two materials would compromise the ability to detect and manipulate quantum states. The properties of these hybrid junctions are affected by the interface purity within the heterostructure, where the presence of oxides, impurities, or structural defects is a detrimental source of noise and dissipation in these material systems.(2)
The goal of this PhD thesis is to develop a scalable material platform where quantum properties can be engineered simply by tailoring the crystal structure of a single atomic element – Tin (Sn) – and achieve interfaces with the highest quality. Topological insulator/topological semimetal phases can be tailored in diamond cubic a-Sn by controlling strain,(3) while body-centered tetragonal ß-Sn behaves as a superconductor at temperatures below 4 K.(4) Currently, a controlled switch between a/ß-Sn phases is out of reach using a conventional thin film geometry.
The PhD student will establish the growth of one-dimensional (1D) Sn nanowires (NWs) on a Silicon wafer using a molecular beam epitaxy (MBE) system. NWs offer the ideal system to control the crystalline phase of a material without nucleating structural defects.(5) In this thesis, this crystal-phase engineering paradigm will be developed for group IV NWs to achieve a precise control over the growth of a-Sn and ß-Sn phases (i.e. TOP and SC phases). This protocol will then enable the growth of defect-free a/ß-Sn NWs with atomically-sharp interfaces and with the highest structural quality. This nanostructured material will provide a truly homogeneous integration of multiple states of matter in solid-state quantum devices, paving the way to explore the fundamental processes in topological quantum computation,(6) spintronics,(7) and quantum photonics.(8)
The student will investigate the structural properties (scanning electron microscopy, atomic force microscopy, transmission electron microscopy, X-ray diffraction, atom probe tomography) and optical properties (Raman) of the a/ß-Sn NWs using a variety of characterization techniques available at CEA. To demonstrate the presence of TOP or SC phases in these nanomaterials, the student will fabricate a NW field-effect transistor (FET) (single NW transfer to a SiO2/Si substrate, electron beam lithography, metals and oxides deposition). Next, magnetotransport measurements at cryogenic temperatures (1 K or less) will be performed to demonstrate the TOP behavior in a-Sn and SC state in ß-Sn. This thesis will train the student with a diverse skillset ranging from materials growth, structural and optoelectronic characterization, device fabrication, and quantum transport measurements.
(1) P. Liu et al., Nat. Rev. Mater. 4, 479–496 (2019).
(2) N. P. de Leon et al., Science 372, 1–20 (2021).
(3) A. Barfuss et al., Phys Rev Lett. 111, 157205 (2013).
(4) Y. Zhang et al., Sci Rep. 6, 32963 (2016).
(5) S. Assali et al., Nano Letters. 15 (12) (2015).
(6) A. Stern, N. H. Lindner, Science. 339, 1179-1184 (2013).
(7) J. Ding et al., Advanced Materials. 33, 2005909 (2021).
(8) E. D. Walsh et al., Science. 372, 409-412 (2021).