Young Graduate Trainee Machine Learning

hace 2 semanas

Madrid, Madrid, España European Space Agency A tiempo completo

EUROPEAN SPACE AGENCY
Young Graduate Trainee Machine Learning & Accessibility for Space Science

Job Requisition ID:18397
Closing Date:7 March :59 CET/CEST
Publication:External Only
Vacancy Type:Young Graduate Trainee
Date Posted:8 February 2024- Young Graduate Opportunity in the Directorate of Science This post is classified F1 on the Coordinated Organisations' salary scale.
Location

  • ESAC, Villanueva de la Cañada, Spain
    Our team and mission
The European Space Agency maintains a world-leading Science Programme with missions in heliophysics, planetary science, astrophysics and fundamental physics. Its mission is to 'Empower Europe to lead space science'.

The Department for Science and Operations (SCI-S), within ESA's Directorate for Science, host the scientists and engineers that oversee the space missions from study to end of operations; it develops the science operation systems for the missions and operates the missions in space; it archives and curates their data during operations and beyond.

Our main objective is to maximise the scientific output of the missions for the benefit of humankind.

The traineeship is placed at the Data Science and Archives Division of the Science and Operations Department and aims to support innovative data science activities with a view to increasing the science return of ESA's science missions through enhancing the science data exploitation, as well as by improving the efficiency of mission science operations.

The division is currently developing a platform to support data analytics initiatives for ESA's space science missions. The platform, ESA Datalabs, is focused on improving collaboration and enabling easy access to data for scientific exploitation. However, there are many opportunities to extend its functionality.

Field(s) of activity/research for the traineeship
The section is actively working on testing and integrating state-of-the-art machine learning and data science methods in the platform.

Further, this position is focused on investigating diverse data analysis and representation methods to jointly improve science exploitation while also improving the accessibility of science data and ESA platforms for people with physical disabilities.


Hence, the activities will include:
- working on maximizing science exploitation using state-of-art machine learning and date science methods
- exploring recent advances in fields such as natural language processing, semi-supervised / zero-shot learning and physics-based neural networks
- testing and helping to improve accessibility of ESA's science platforms such as ESA Datalabs for people with physical disabilities
- exploring different tools and methodologies in data visualization and presentation to improve accessibility and enhance scientific study using methods such as sonification or others.

Technical competencies
Knowledge of relevant technical domains
Relevant experience gained during internships/project work
Breadth of exposure coming from past and/or current research/activities
Knowledge of ESA and its programmes/projects

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 computer science, physics, astronomy, data science or similar.


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.


You should also have:

  • Knowledge or interest in datadriven astronomy or other physical sciences
  • Knowledge or interest in machine learning and data science
  • Knowledge or interest in the presentation of scientific data for a diverse audience
  • Firsthand experience with accessibility and/or astronomy for people with physical disabilities

Would be an asset:

  • Experience in a programming language (Python, R, MATLAB,)
  • Experience with machine learning frameworks (PyTorch, TensorFlow,)
  • Experience or interest in inclusive design
  • Experience or interest in open science, open source, or citizen science
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 ProgrammeMember States, Associate Members or Cooperating States.

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