Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
-
Field
-
and conducting work in the modelling of EEPS (scene generators, geometry module, spacecraft, payload, forward and retrieval algorithms, level 0 to level 1 algorithms, etc.); initiating and conducting
-
with established causal models. Ultimately, you will design algorithms for causality-based analysis and counterfactual recovery of liveness violations. Information and application Are you interested in
-
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
-
studies independently, working with diverse datasets, developing algorithms and decision rules, and contributing to the refinement of data-driven intervention strategies. Tasks As a postdoctoral researcher
-
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
-
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
-
processing; ensuring the provision of necessary instrument inputs for the development of level 1 processing tools/algorithms and the associated ground processor prototype; ensuring the timely availability
-
on the resulting algorithms and pipelines. As an emerging paradigm, differentiable programming builds upon several areas of computer science and applied mathematics, including automatic differentiation, graphical
-
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
-
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