98 machine-learning "https:" "https:" "https:" "UCL" positions at European Space Agency
Sort by
Refine Your Search
-
diplomatic network and managing the VIP participation to launch events with the support of the communication services. You are encouraged to visit the ESA website: http://www.esa.int Field(s) of activity
-
conjunction with an enhanced visualization of their output and performance (e.g. through dedicated cockpits and Key Performance Indicators). You are encouraged to visit the ESA website: http://www.esa.int Field
-
space ambitions, delivering tangible, measurable and long-term impact for future missions. You are encouraged to visit the ESA website: http://www.esa.int Field(s) of activity/research for the traineeship
-
advanced techniques (such as digital beamforming or machine learning/Al techniques) supporting instrument operation and operative modes; onboard data compression; onboard data encryption; ASICs and devices
-
are encouraged to visit the ESA website: http://www.esa.int Field(s) of activity/research for the traineeship As an ESA Graduate Trainee, you will support the HR Department's teams dealing with
-
on the optimisation of the data architecture to enable the efficient use of artificial intelligence and machine learning. Duties These positions combine EO domain knowledge (EO instruments, EO data, EO algorithms
-
interested are encouraged to visit the ESA website: http://www.esa.int Field(s) of activity for the internship Topic of the internship: Propulsion Test Bench Your internship is composed of three parts
-
Knowledge of EO space mission operations and operations planning Knowledge of specific characteristics of military and dual use space systems Behavioural competencies Education A master's degree in
-
characteristics of military and dual use space systems Behavioural competencies Education A master's degree in engineering or a scientific discipline is required for this post. Additional requirements You should
-
or hands-on hardware (including integration) experience Artificial Intelligence and Machine learning techniques for AOCS applications and engineering The motivation for supporting engineering laboratory