Intern in the Data Analysis of ACES Mission

Contribute to data analysis activities of the ACES mission.

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ESA - European Space Agency

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Application deadline 7 months ago: Sunday 30 Nov 2025 at 23:59 UTC

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Overview

Contribute to data analysis activities of the ACES mission.

You have:

  • You must be a university student, preferably studying at master’s level.
  • A good knowledge of English or French is required.
  • Knowledge and background in time and frequency analysis, signal processing, and orbital mechanics are an asset.
  • Prove that you will be enrolled at your University for the entire duration of the internship.

Contract

This is a Internship contract. It usually requires 0 years of experience, depending on education. More about Internship contracts.

Location ESTEC, Noordwijk, Netherlands

Our team and mission

HRE-SU (Utilisation and Enabled Science) team at ESA coordinates the Agency’s research programme in physical sciences and biology under microgravity conditions and for space exploration. Using platforms like the International Space Station, as well as Moon and Mars missions, the team supports a wide range of cutting-edge research—from Earth atmospheric studies and quantum sensors to heat transfer phenomena, soft matter, and advanced materials processing.

This internship opportunity is embedded as part of the ongoing scientific operations of the Atomic Clock Ensemble in Space (ACES) mission. The ACES payload comprises a cold-atom cesium clock (PHARAO), a hydrogen maser (SHM), a high-performance two-way microwave link (MWL), and the European Laser Timing (ELT) system. Together, these instruments enable ultra-precise time and frequency comparisons between space-based and ground-based clocks. Launched in April 2025 and installed on the Columbus module of the International Space Station, ACES is currently in its commissioning phase, during which payload performance is being rigorously evaluated and calibrated.

Candidates interested are encouraged to visit the ESA website: http://www.esa.int

Field(s) of activity for the internship

Topic of the internship: Data analysis support for the ACES mission

You will contribute to the data analysis activities of the ACES mission, focusing on its two core objectives: advancing global time and frequency metrology, and testing fundamental physics—most notably the gravitational redshift predicted by general relativity. Your primary role will involve supporting the data analysis of the MWL, which enables precise time transfer between the space-based clock ensemble and multiple ground stations simultaneously. The link operates in a three-frequency, bi-directional, asynchronous configuration, with signals modulated by pseudo-random codes and tightly phase-locked to ultra-stable onboard and ground-based clocks. These signals are used to extract the relativistic time signature, which must be disentangled from a combination of light-time propagation effects, instrumental delays, orbital dynamics, and measurement noise.

With regard to the mission objectives, the low, circular orbit of the International Space Station presents both opportunities and challenges. On one hand, it allows frequent daily passes over ground stations, providing a dense and globally distributed dataset ideal for metrology. On the other hand, the gravitational redshift signal is only weakly modulated in such an orbit, requiring an absolute measurement between the space clock PHARAO and cesium fountain clocks on the ground. This requires coherent phase concatenation between successive ISS passes and monitoring of dynamic effects such as Doppler rate variations, signal amplitude-related phase shifts (AM to PM conversion), and variations in received power. You will support efforts to refine and apply these calibrations in a variety of scenarios and contribute to the ongoing development, testing, and validation of the data processing algorithms. There may also be opportunities to assist in orbit determination tasks and in studying how the MWL and ELT links can be jointly used to improve the calibration of internal delays.

Specific tasks may include:

  • Implementing and validating calibration procedures to preserve phase continuity and correct instrumental effects;
  • Processing microwave link observables in an orbit determination framework to derive desynchronisation and range;
  • Supporting the identification and interpretation of relativistic time transfer signatures;
  • Contributing to the synergy between the microwave and optical links for improved delay calibration.

Learning objectives:

  • Develop an understanding of spaceborne atomic clocks and high-precision time and frequency transfer techniques;
  • Gain hands-on experience with data analysis, signal processing, and time series modelling;
  • Learn to apply calibration techniques in the context of complex space instrumentation;
  • Engage directly with ongoing research in fundamental physics and global timekeeping networks.

Crucially, you shall also strengthen your programming skills by developing and maintaining Python-based tools for processing and analysing MWL data: this includes modular code design, data handling, visualisation, and documenting workflows to ensure reproducibility and scientific traceability. In parallel, you will foster strong research skills in critical thinking, comparative analysis, and scientific reporting. This internship offers a unique opportunity to work with real mission data from a pioneering experiment in space-based physics and metrology, within a collaborative and multidisciplinary environment at the leading edge of scientific metrology and space science.

Behavioural competencies

Result Orientation Operational Efficiency Fostering Cooperation Relationship Management Continuous Improvement Forward Thinking

For more information, please refer to ESA Core Behavioural Competencies guidebook

Education

You must be a university student, preferably studying at master’s level. In addition, you must be able to prove that you will be enrolled at your University for the entire duration of the internship.

Additional requirements

The working languages of the Agency are English and French. A good knowledge of one of these is required. Knowledge of another ESA Member State language is an asset.

During the interview, your motivation for applying to this role will be explored.

Knowledge and background in time and frequency analysis, signal processing, and orbital mechanics are an asset.

Diversity, Equity and Inclusiveness ESA is an equal opportunity employer, committed to achieving diversity within the workforce and creating an inclusive working environment. We therefore welcome applications from all qualified candidates irrespective of gender, sexual orientation, ethnicity, religious beliefs, age, disability or other characteristics.

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 via email at [email protected].

Important Information and Disclaimer During the recruitment process, the Agency may request applicants to undergo selection tests.

Applicants must be eligible to access information, technology, and hardware which is subject to European or US export control and sanctions regulations.

The information published on ESA’s careers website regarding internship conditions is correct at the time of publication. It is not intended to be exhaustive and may not address all questions you would have.

Nationality

Please note that applications are only considered from nationals of one of the following States: Austria, Belgium, Czechia, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, the Netherlands, Norway, Poland, Portugal, Romania, Slovakia, Slovenia, Spain, Sweden, Switzerland, and the United Kingdom.

Potential interview questions

Can you describe your experience with data analysis in complex systems? This question assesses your familiarity with handling intricate datasets. Provide specific examples of your past work, focusing on techniques used and results achieved.
How do you prioritize tasks when working on multiple projects? This helps evaluate your organizational skills and ability to manage time effectively. Pro members can see the explanation.
Describe a situation where you had to learn a new skill quickly to solve a problem. Pro members can see the explanation. Pro members can see the explanation.
What interests you about working on the ACES mission? Pro members can see the explanation. Pro members can see the explanation.
Explain how you would approach a complex data processing task. Pro members can see the explanation. Pro members can see the explanation.
How would you handle discrepancies in data during analysis? Pro members can see the explanation. Pro members can see the explanation.
What is your understanding of gravitational redshift and its significance? Pro members can see the explanation. Pro members can see the explanation.
How do you ensure scientific traceability in your work? Pro members can see the explanation. Pro members can see the explanation.
Added 8 months ago - Updated 7 months ago - Source: jobs.esa.int