Internal Research Fellow (PostDoc) in Onboard Data Handling for Cognitive Cloud Computing in Space Job Requisition ID: 20565 Date Posted: 13 May 2026 Closing Date: 3 June :59 CET/CEST Publication: External Only Type of Appointment: Internal Research Fellow Directorate: Earth Observation Programmes Workplace: Frascati, IT Location: ESRIN, Frascati, Italy Reporting to the Head of the Explore Office in the ESA Phi-lab, you will work in close cooperation with other staff in the Directorate of Earth Observation Programmes and with staff in the Avionics and EEE Division within the Directorate of Technology, Engineering and Quality. You may also collaborate with scientists and engineers in other divisions of ESA. You will be part of the ESA Phi‑lab. Our mission is to accelerate the future of Earth Observation (EO) by embracing disruptive innovation and serve as the catalyst for transformative innovation in the sector. Our vision is to become an EO innovation hub, connecting EO with a growing ecosystem of disruptive and transformative innovation, including AI, machine learning, quantum computing, edge computing, metamaterials and photonics. Many of the challenges posed by new technologies need to be tackled at scientific, application and capability levels to deliver the maximum value from satellite‑derived EO assets for climate, society and economy. The Phi‑lab will bring together early‑career and senior researchers from a variety of disciplines across EO and disruptive/transformative innovation to contribute to the development of innovative EO solutions. A stimulating multinational, interdisciplinary and open work environment; Access to high‑performance computing infrastructure and unparalleled EO and technology expertise; A unique opportunity to work on innovative solutions to address global challenges; Freedom and focus to conduct creative research while making an impact in relation to ESA’s strategy; A wide network of relationships and collaboration with top academia, industry and research centres; The opportunity to contribute to the Phi‑lab strategy and activities. As an internal research fellow within the Phi‑lab, you will invest your time mainly in the agreed research topics, but will also provide support to the Phi‑lab’s industrial and internal activities, mentor members of our research network and engage in outreach activities, all generally but not exclusively related to your research topic. Field(s) of activity/research: Cognitive Cloud Computing in Space (3CS) – the integration of AI, novel computing paradigms such as cloud computing and edge computing, computing hardware and other technologies on board space systems. The research activity aims to build efficient data handling processing chains for EO 3CS missions, with a focus on hardware and architectural elements and prototyping. It will analyse 3CS‑enabled novel mission paradigms and observation strategies, derive their main requirements, and investigate the design of the most efficient data processing chains and the most suitable hardware elements. It will also investigate potential advantages brought about by the use of innovative computing paradigms in the implementation of such processing chains. Potential Research Topics (at least one focus): Efficient data handling processing chains: design of onboard data handling processing architectures for 3CS‑enabled missions for EO, exploring hardware and software solutions for complex AI models, data fusion, AI model training, and architectures like mass‑memory‑centered and online processing. Standardisation of hardware‑software interfaces: defining modular, standardised interfaces for seamless integration of emerging hardware accelerators into existing space processing pipelines. Hardware‑aware and trustworthy training pipelines for edge AI: developing edge AI models for EO systems with a focus on hardware‑aware efficiency and trust and compliance, designing for mission‑critical systems with explainability and adherence to the European AI Act. Disruptive computing paradigms for onboard data processing: designing, prototyping and benchmarking onboard data processing chains at both hardware and software levels, based on disruptive computing paradigms such as photonic and neuromorphic computing. Cyber security for onboard AI model robustness: designing robust data processing pipelines for AI‑based onboard processing to prevent data manipulation or adversarial attacks. As part of your application, please provide a research proposal of no more than five pages relating to the development of efficient data handling processing (both hardware and software) for 3CS‑enabled EO missions. The proposal should: describe the main research questions, propose a research plan with methodology, describe your previous experience, reference EO 3CS mission paradigms, specify main hardware devices and computing paradigms, provide a possible schedule, and mention any additional methodological elements. In particular, you will: undertake advanced research activities exploring and expanding the use of disruptive and transformative innovation such as AI, machine learning, quantum computing and edge computing to develop new frameworks and solutions; support the definition and implementation of rapid prototyping activities, research sprints and open challenges of innovative EO solutions; engage with the innovation ecosystem to promote the uptake of new techniques and capture the latest developments in EO and disruptive/transformative innovation; publish the research project outcomes in high‑impact journals; drive collaboration within the Phi‑lab community and ESA internal teams to promote the uptake of these new techniques and solutions; contribute to the Phi‑lab strategy, activities and outreach on disruptive technologies for EO; maintain a continuous dialogue with the scientific community, including major international programmes and initiatives in the field; support the Phi‑lab’s daily activities and the research network of ESA graduate trainees, national trainees, interns and visiting professors, experts and researchers, as applicable; collaborate closely with ESA’s Phi‑lab and Avionics and EEE Division on the identification, testing and benchmarking of hardware components for edge computing and learning; conduct research and implement prototypes of 3CS‑based efficient processing chains for 3CS missions; support ESA’s Phi‑lab staff with external R&D activities relating to onboard AI and 3CS. Technical competencies: Knowledge relevant to the field of research; Research/publication record; Ability to conduct research autonomously; Breadth of exposure coming from past and/or current research/activities; Ability to gather and share relevant information; General interest in space and space research. Behavioural competencies: Result orientation; Operational efficiency; Fostering cooperation; Relationship management; Continuous improvement; Forward thinking. Education: You should have recently completed, or be close to completion of, a PhD in a related technical or scientific discipline. Preference will be given to applications submitted by candidates within five years of receiving their PhD. In particular, PhD in electronics, embedded systems, computer science, AI, machine learning, aerospace engineering, Earth system science or climate, with a thesis subject relevant to the above description of tasks. Additional Requirements: In addition to your CV and motivation letter, please prepare a research proposal of no more than 5 pages. Experience with hardware benchmarking for edge computing (e.g., FPGAs, TPUs, VPUs, GPUs) and edge learning paradigms; Experience in the design of edge computing data processing chains; Sound knowledge of computing architectures (e.g., RISC, CISC, SIMD, VLSI processes, edge AI design flow, embedded systems, machine learning and data science); Basic knowledge of onboard AI, 3CS concepts, satellite systems and space missions; The ability to think outside the box and explore new avenues, with natural curiosity and a passion for new subjects and research areas; Basic knowledge of AI agents and large language models; Experience with one or more general‑purpose programming languages (e.g., Python) and general‑purpose deep learning frameworks (e.g., TensorFlow, PyTorch); Interest in and ability to share knowledge with other ESA organisational units. The following elements are considered an asset: Knowledge of edge learning paradigms such as distributed learning and federated learning; Basic knowledge of EO data processing chains for optical and/or SAR data (e.g., level 0/level 2); Knowledge of communication protocols (e.g., Ethernet, PCIe, SpaceWire, SpaceFibre); Previous experience with edge computing systems based on disruptive computing paradigms (e.g., neuromorphic computing, photonic computing); Previous experience with ASIC/FPGA design; Knowledge of AI security at hardware and software levels. You should also have good interpersonal and communication skills and should be able to work in a multi‑cultural environment, both independently and as part of a team. Your motivation, overall professional perspective and career goals will also be explored during the later stages of the selection process. ESA is an equal‑opportunity employer, committed to achieving diversity within the workforce and creating an inclusive working environment. We welcome applications from all qualified candidates irrespective of gender, sexual orientation, ethnicity, religious beliefs, age, disability or other characteristics. Whenever possible, we seek to accommodate individuals with disabilities by providing the necessary support at the workplace. If you would like to discuss this further, contact the Human Resources Department at Nationality and Languages: Applicants can only be considered from nationals of the following states: Austria, Belgium, Czechia, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Luxembourg, the Netherlands, Norway, Poland, Portugal, Romania, Slovenia, Spain, Sweden, Switzerland, and the United Kingdom. Nationals from Cyprus, Latvia, Lithuania and Slovakia (Associate Member States), Canada (Cooperating State), Bulgaria, Croatia and Malta (European Cooperating States) can also apply. The working languages are English and French; good knowledge of one of these is required, and knowledge of another Member State language would be an asset. #J-18808-Ljbffr