10 deep-learning positions at European Space Agency

Young Graduate Trainee in High-Performance Computing - AI/GPU Optimisation and Parallelisation

workloads on ESA's HPC resources. This includes distributed training and inference of deep learning models, as well as exploiting the full potential of GPU nodes through techniques such as mixed-precision

Internal Research Fellow (Post-Doctoral) in Disruptive Innovation for Green and Sustainable Future

languages (e.g. Python) and with general purpose deep learning frameworks (e.g. Tensorflow or PyTorch) the ability to share knowledge with other ESA units You should have good interpersonal and communication

Internal Research Fellow (Post-Doctoral) in AI Onboard for Synthetic Aperture Radar (SAR) Missions

experience with one or more general purpose programming languages (e.g. Python) and with general purpose deep learning frameworks (e.g. Tensorflow or PyTorch) the ability to share knowledge with other ESA

Galileo Constellation Deployment and Replenishment Architect

maintenance and evolution of the tools described above in order to maintain a complete overview and control of the Unit’s software infrastructure; Generating lessons learned and contributing to the knowledge

Young Graduate Trainee in CubeSat Systems Engineering

participation in the ongoing CubeSat projects with industry/research institutes, including those targeting lunar and deep space missions (e.g. near-Earth asteroid rendezvous, distant retrograde orbit etc.). As a

Young Graduate Trainee in Optical and Quantum Communication

-generation communication networks, namely deep space optical communication network or space-based quantum communication network. You will be exposed to and learn about development process of innovative optical

Young Graduate Trainee in AI Data Protection Engineering

, as well as experience with deep learning frameworks (e.g., TensorFlow, PyTorch) is highly desirable. Strong analytical and problem-solving skills, with the ability to analyse data, identify patterns

Head of the Future Programmes Office

area of responsibility. Technical competencies Experience in space systems engineering with a systems orientation and an end-to-end view of satellite navigation projects Deep technical knowledge

Young Graduate Trainee in Satellite Telecommunications and TT&C

-Earth and deep space missions, equipment, technology, protocol, signal design, receiver and signal processing, etc. The work may entail simulations using or upgrading existing simulators in MATLAB/Python

Young Graduate Trainee in Next Generation Ground Systems for New Space

area expertise in one or multiple of following domains is an asset: AI (Machine and Deep learning), Cyber Security, AR/VR technologies, Optical Communication, RF, Embedded software development