European Space Agency (ESA)
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JOB DESCRIPTION
Location
ESTEC, Noordwijk, Netherlands
Our team and mission
The Radio Frequency Payloads & Technology Division (TEC-EF) is responsible for RF payloads, instruments and technologies for space and ground applications, including all equipment having a Radio Frequency space/ground interface and its associated Laboratories. The division supports the definition, specification and development/ procurement of laboratories either for ESA projects and technology programmes or external customers.
Within the TEC-EF Division, the RF Payload Engineering and Digital equipment Section responsibilities encompasses payloads and instruments with Radio Frequency interface for telecommunication, remote sensing and navigation exploiting different technologies (e.g. analogue, digital, optical) including design and performance analysis tools and testing and digital functions.
Additionally, the section covers the research, design, development and testing of Radio Frequency Digital equipment for telecommunication/navigation payloads and RF/microwave and millimetre wave remote sensing instruments, as well as Payload Signal and Data Processing techniques.
You are encouraged to visit the ESA website: http://www.esa.int
Field(s) of activity/research for the traineeship
You will have the opportunity to contribute in one of the following disciplines, depending on your background and interests:
- Machine Learning techniques for RF Payloads and Instruments: Evaluation of Machine learning techniques for future RF payloads and instruments, with a focus on on-board processing for Earth observation missions. Possible applications include intelligent data compression, cognitive radars, adaptive beamforming and steering, anomaly detection including radio frequency interference identification and instrument performance prediction, raw SAR data information extraction and image formation, and others. Concepts in the frame of Satellite Communication missions like cognitive radio or intelligent regenerative processors could also be investigated. You will study Machine Learning techniques and hardware accelerators for one or more applications relevant to RF payloads and microwave instruments. You will target the implementation of a use-case based on a relevant dataset.
- Efficient signal processing algorithms and architectures for Telecommunication Payloads: Considering contemporary processor architectures, data converters, programmable logic, and accelerators, you will develop Digital Signal Processing (DSP) algorithms for the processing of the communication spectrum. This includes tasks such as channelisation, data routing, beamforming, and functions to support modem operations. You will research and implement DSP solutions to enhance processing efficiency per watt at speeds associated with high- throughput satcom missions. You will also carry-out hands-on work in the lab for this activity.
- Advanced Remote Sensing Instruments: Design, modelling, analysis and performance assessment of future earth observation remote sensing instruments. These instruments include wide-swath Synthetic Aperture Radars, wide- swath Radar Altimeters and/or Scatterometers. The trainee will assess novel instrument architectures and establish performance trade-offs.
Technical competencies
Behavioural competencies
Result Orientation
Operational Efficiency
Fostering Cooperation
Relationship Management
Continuous Improvement
Forward Thinking
Education
You should have just completed or be in the final year of your master’ s degree in Telecommunications/Electronic/Microwave/Computer Science Engineering.
Additional requirements
You should have good interpersonal and communication skills and should be able to work in a multicultural environment, both independently and as part of a team.
Specific competence in one of the following disciplines shall be considered an asset:
- Analog and digital signal processing and/or radio frequency and digital sub-systems.
- On-board processing
- Machine Learning and AI
- Knowledge and/or experience in computer programming (e.g. Matlab).
The working languages of the Agency are English and French. A good knowledge of one of these is required. Knowledge of another Member State language would be an asset.
During the interview motivation and overall professional perspective/career goals will also be explored.
Other information
For behavioural competencies expected from ESA staff in general, please refer to the ESA Competency Framework.
For further information on the Young Graduate Programme please visit: Young Graduate Programme and FAQ Young Graduate Programme
At the Agency we value diversity and we welcome people with disabilities. Whenever possible, we seek to accommodate individuals with disabilities by providing the necessary support at the workplace. The Human Resources Department can also provide assistance during the recruitment process. If you would like to discuss this further please contact us email [email protected].
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Please note that applications are only considered from nationals of one of the following States: Austria, Belgium, the Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Luxembourg, the Netherlands, Norway, Poland, Portugal, Romania, Spain, Sweden, Switzerland, and the United Kingdom. Nationals from Latvia, Lithuania, Slovakia and Slovenia, as Associate Member States, or Canada as a Cooperating State, can apply as well as those from Bulgaria, Croatia and Cyprus as European Cooperating States (ECS).
According to the ESA Convention, the recruitment of staff must take into account an adequate distribution of posts among nationals of the ESA Member States*. When short-listing for an interview, priority will first be given to candidates from under-represented Member States*.
In accordance with the European Space Agency’s security procedures and as part of the selection process, successful candidates will be required to undergo basic screening before appointment conducted by an external background screening service.
*Member States, Associate Members or Cooperating States.
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