Postdoctoral Position

Position description **Category**: - Mathematics, information, scientific, software **Contract**: - Fixed-term contract **Job title**: - Postdoctoral Position : Researcher in Artificial Intelligence applied to microfluidic H/F **Socio-professional category**: - Executive **Contract duration (months)**: - 12 **Job description**: - This postdoctoral position is part of the 2FAST project (Federation of Fluidic Autonomous labs to Speed-up material Tailoring). It focuses on accelerating chemical synthesis through continuous and miniaturized methods like microfluidics and flow chemistry. These techniques offer precise control over experimental conditions and leverage digital advancements for improved research outcomes in material chemistry. By utilizing databases, A.I., and real-time measurements, synthesis routes can be optimized, although the comprehensive characterization of nano/micro-materials remains challenging due to cost and complexity. Despite the lack of a universal approach to continuous chemical processes, the project aims to exploit digitalization in microfluidics laboratories, collaborating with experts in chip’s design and analytical techniques. Together, we will develop interoperable microfluidic chips to control material properties during synthesis. The postdoctoral project will focus on the orchestration aspect of the autonomous lab-on-a-chip. The main tasks will be: - Designing, creating and evaluating feedback loops thanks to active learning models enabling to build correlations between control parameters (e.g. concentration of a reagent) and the collected signals (UV-Vis spectrum). At least, two feedback loops will be developed and compared, one based on classical optimization approaches, one based on reinforcement-based machine learning methods. - Take part in the creation of a signal database adapted to machine learning methods particularly on the implementation of auto-encoder networks (e.g. GANs) to simulate signals and/or format the database. - Implementing machine learning methods to connect "highly resolved data" to more readily available observables, and demonstrate the possibility to connect, desired nanoparticle properties and synthesis conditions. - Managing interactions within the interdisciplinary team and also with external collaborations for A.I. implementation. - Articles and reports writing '2FAST is one of the targeted projects of the PEPR (Priority Research Programs and Equipment) project DIADEM. DIADEM is a comprehensive initiative aimed at accelerating the design and manufacturing of more efficient and sustainable materials. The appointed researcher will join an excellence network comprising four different laboratories at the national level: ICMCB (UMR5026) and LOF (UMR5258) in Bordeaux, LGC (UMR5503) in Toulouse, ISEC (CEA) in Marcoule, and LIONS (UMR 3685) in Paris Saclay.**Applicant Profile**: - Bac + 8- Doctorat- Spécialités : A.I or related fields : A.I., Machine learning, Microfluidic, programming, numerical silumation- Programming languages : Pytho, C++Position location **Site**: - Marcoule **Job location**: - France, Occitanie, Gard (30) **Location**: - Bagnols sur Cèze **Languages**: - English (Intermediate) **Recommended training**: - PhD : A.I or related fields Requester **Position start date**: - 01/09/2024 General information **Organisation**: The French Alternative Energies and Atomic Energy Commission (CEA) is a key player in research, development and innovation in four main areas: - defence and security, - nuclear energy (fission and fusion), - technological research for industry, - fundamental research in the physical sciences and life sciences. Drawing on its widely acknowledged expertise, and thanks to its 16000 technicians, engineers, researchers and staff, the CEA actively participates in collaborative projects with a large number of academic and industrial partners. The CEA is established in ten centers spread throughout France **Reference **:2024-32778**Division description**: - Le DMRC est chargé des activités de recherche pour concevoir, développer et simuler les procédés physico-chimiques et les technologies mis en œuvre dans l'amont et l'aval du cycle du combustible nucléaire. Dans le cycle du combustible, ses activités couvrent les domaines de la mine et du recyclage du combustible (amont et aval du cycle). Les compétences initialement développées pour le nucléaire sont désormais également mobilisées pour développer des procédés de purification et de recyclage des métaux stratégiques en soutien au développement de nouvelles filières industrielles. **Description de l'unité**: - Le Service des Technologies Durables pour le Cycle des matières (STDC) a pour mission d'amplifier le développement des technologies durables pour les systèmes énergétiques décarbonés (nucléaire et énergies renouvelables). L'un de ses principaux enjeux est de positionner le CEA comme acteur majeur d