Quasar Science Resources S.L.
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Pic legend 1: Robotic Test Bed Telescope (TBT), La Silla, Chile
Pic legend 2: Autonomous Emergency System (AES) designed by Quasar for the Robotic Test Bed Telescope (TBT) ESA project
Pic legend 3: Global turbidity model
Pic legend 4: Cartography of Coastal Marine Ecosystem
General information
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Company nameQuasar Science Resources S.L.
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AdressCamino de las Ceudas 2, 28232, Las Rozas de Madrid, Madrid
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Turnover1.77 million EUR in year 2024
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Employees21 in year 2024
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SMEYES
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Contact Info:
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Phone+34918197120
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Emailcontact@quasarsr.com
Activity and Skills
Quasar Science Resources, S.L. is a recently formed private company that provides consulting Software and System Engineering services for Research and Development projects. Quasar provides high quality tailored-made services targeted at Research Centres, Universities and Private Companies looking to expand their activity domain.
We operate in Madrid (Spain) area but our customers include national and European partners both in the public and private sectors. Quasar has strong expertise in scientific software development and data reduction techniques, handling and exploitation of scientific databases, archive engineering and data mining, computer systems engineering, including virtual machine infrastructure, network, data storage and backup. Quasar has ample experience working in international collaborations in the fields of ground and space-based scientific astronomical observatories.
Quasar has presence at the European Space Astronomy Centre (ESAC) within the Frame Contracts for Industrial Support to ESA. The work at ESAC focuses on four main areas: Science Operations Support, Software Engineering, Development and Maintenance Support, IT Support to Scientific Missions and the ESA Science Data Centre.
In 2018 Quasar was accepted into the ESA Business Incubation Centre (BIC) Madrid Region for two years with the SIMBAD project. SIMBAD (Sentinel Imagery MultiBand Analysis and Dissemination), is a module of our Scientific Exploitation Platform dedicated to the processing of Sentinel imagery and the extraction of EO-based products.
Quasar has expertise in the field of SSA, especially in the field of optical robotic telescopes.
Contracts for Big Science facilities
[OTHER - YEBES OBSERVATORY]
Technical assistance for software development and the implementation of a system for the exploitation, visualization, and public service of the data from the 40m radio telescope at the Yebes Observatory
(2023 - 2025)
Financed by the Recovery, Transformation, and Resilience Plan funded by the European Union Next Generation EU.
[ESA]
S1-PD-06.2 - Software Development for NEO Observational Activities
(2022 - 2024)
To improve and maintain the ESA’s Test-Bed Telescope’s (TBT) software; and to develop a service to support astronomers with ArtSat/NEO identification.
[OTHER - YEBES OBSERVATORY]
Technical assistance for the commissioning of an astronomical and geodesic correlator for RAEGE and EU-VGOS at the Yebes Observatory
(2022 - 2023)
Procurement of technical assistance for the implementation of an astronomical and geodetic correlator for RAEGE and EU-VGOS at the Yebes Observatory as part of the YNART project co-financed with FEDER funds.
[ESA - DEIMOS SPACE]
S1-PD-10 Software Maintenance
(2021 - 2024)
Maintenance, including the provision of support to operations, of the NEOCC for what concerns the continued availability and usage of the NEO data systems.
[OTHER - CNES]
Share My Space - Automation and autonomous onboard system for collision risk management
(2020 - 2022)
Identify the need and the feasibility of automating the collision risk management process for a wide range of satellite missions.
[ESA]
SSA P3-NEO-I B - Installation and Commissioning of TBT2 in La Silla
(2019 - 2022)
Installation and commisioning of the Test Bed Telescope at La Silla Observatory in Chile.
Relevant R&D projects
[MICIN Industrial PhD] DIN2024-013348 - Assessment of the Impact of aquaculture activities on the quality of coastal waters using earth observation data.
(AQUALIA)
(2025)
The general objective of this project is to employ satellite remote sensing techniques for the development of independent and fully automated routines for real-time detection, characterization, and monitoring of the shallow marine environment, with particular emphasis on industrial sectors such as aquaculture, which have a large-scale, yet unevaluated impact on the environment.
Industrial doctorate programme of the Ministerio de Ciencia, Innovación y Universidades, in collaboration with Universidad de Valencia, DIN2024-013348.
[CAM Industrial PhD] IND2022/BIO-23597 - Development of real-time wildfire risk mapping for the Community of Madrid using remote sensing data.
(Risk4Fire)
(2023)
Development of real-time wildfire risk mapping for the Community of Madrid using remote sensing data.
Industrial doctorate programme, IND2022/BIO-23597.
[CAM Industrial PhD] ND2020/AMB-17747 - Evaluation of agricultural systems by means of satellite remote sensing time series and dynamic prediction models
(2020 - 2024)
Evaluation of agricultural systems using remote sensing time series and dynamic prediction models.
Industrial doctorate programme, ND2020/AMB-17747.
[MICIN Industrial PhD] DIN2020-010979 - Algorithms and models to characterize the quality of coastal waters using satellite remote sensing techniques
(2020)
Algorithms and models to characterize the quality of coastal waters using satellite remote sensing techniques.
Industrial doctorate programme of the Ministerio de Ciencia, Innovación y Universidades, in collaboration with Universidad de Cádiz, DIN2020-010979.
[CAM Industrial PhD] IND2019/TIC17146 - Quantum Artificial Intelligence techniques in reinforcement learning
(QUARTIC)
(2019 - 2024)
Quantum Computing techniques applied to the Artificial Intelligence field in order to solve industry real problems.
Industrial doctorate programme, IND2019/TIC17146.
[Consejería de Educación e Investigación - Comunidad de Madrid] S2017/BMD-3773 - Genetics and Artificial Intelligence Against Obesity
(GenObiA-CM)
(2018 - 2021)
The goal of the project is to develop artificial intelligence, AI, algorithms to utilize socioeconomic, cultural, physical, and nutritional information to predict the risk of obesity and associated health problems.
https://genobia.es/
[ESA BIC - Región Comunidad de Madrid] SIMBAD - A Scientific Exploitation Platform dedicated to the processing of Sentinel imagery and the extraction of EO-based products
(SIMBAD)
(2018 - 2021)
SIMBAD (Sentinel Imagery MultiBand Analysis and Dissemination), is a module of our SEP dedicated to the processing of Sentinel imagery and the extraction of EO-based products. SIMBAD integrates the hardware/software infrastructures able to supply the computing
and storage resources needed for the exploitation and provision of the tools needed to manage the EO datasets in a distributed environment. SIMBAD facilitates the exploitation of EO data by developing applications to address societal challenges, enabling policymakers, authorities, and environmental agencies to develop long-term strategies as well as to react efficiently to
sudden critical situations.
Quasar Science Resources s.l. participates in the esa Business Incubation Centre Madrid region.
https://simbad.quasarsr.com
[Doctorados Industriales de la CAM] IND2017/IND-7793 - Molecular identification by machine learning analysis of Atomic Force Microscopy images
(MAyFAIR)
(2017 - 2021)
Molecular identification by machine learning analysis of atomic force microscopy images.
Industrial doctorate programme, IND2017/IND7793.
[H2020-COMPET-2015] A Gaia and Herschel Study of the Density Distribution and Evolution of Young Massive Star Clusters
(STARFORMMAPPER)
(2016 - 2020)
Grant agreement No 687528 - The key aim of the project is to combine data from two of ESA’s major space missions, Gaia and Herschel, together with ground-based facilities, to constrain the mechanisms that underlie massive star and star cluster formation.
https://starformmapper.org/
[H2020-MSCA-ITN-2015] MSCA-ITN-2015-EID -STARs that 'R' Young: When do stars form in clustered environments?
(STARRY)
(2015 - 2020)
Grant agreement No 676036 - STARRY (STARs that ‘R’ Young) is a twin site European Industrial Doctorate that will provide training to 2 inexperienced researchers in the development of sophisticated research tools in order to exploit, interpret and analyse astronomical data from stateof-the-art observatories in the field of star formation.
https://starry-project.eu/