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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
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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
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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
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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
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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
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-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
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, 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
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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
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-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
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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