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technology model that analyses integrated satellite and ground-based sensor data; estimating European launcher carbon footprint, energy security and energy cost savings; proposing meaningful carbon footprint
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and associated algorithm definition/validation, relevant instrument simulators, quick look systems, the call for proposal system and mission planning systems; Monitoring and supporting the ESA SOC-led
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objectives with societal indicators, geophysical algorithm development and related research activities; supporting the implementation of the renewed ESA EO science strategy and the definition of future
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infrared, as well as quantum sensors. The role of the Future Missions and Instruments Division is to prepare the Earth observation missions, instruments and technologies of the future, encompassing a wide
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intelligence and machine learning technologies/algorithms Background in software engineering and programming languages, data analysis and BI tools Proven experience in technical project and service management
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related to the position: AOCS subsystem architecture, design, testing and verification (including control design algorithms, analysis and simulation) Pointing error engineering Smallsat and nanosat AOCS
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noise sources, charge transfer Inefficiency or persistence on images produced by any imaging detectors (CMOS image sensors, CCDs, MCT hybridised arrays, MKlDs etc.). Pyxel has been developed over the last
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for recognition of planetary materials from multispectral datasets. Interns are sought to contribute to the ongoing development of Machine Learning algorithms for recognition of planetary materials from
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component subsystems and active optical instruments, such as detectors and lasers operating in the UV to FIR wavelength ranges, fibre-optic sensors, lidars, optical communication systems and quantum