Postdoctoral Position in Machine Learning applied to Space Science
Catholic University of Leuven

The researchers will have access to a stimulating research environment within the Mathematics Department of KULeuven and within the network of teams forming the Horizon 2002 project AIDA ( funded by the European commission. Partners include: KU Leuven in Belgium; CWI in The Netherlands; University of Calabria, University of Pisa and CINECA in Italy; CNRS in France; IRIDA in Greece and Space Consulting in USA. The researchers will be employed by KU Leuven, but collaborations with other teams within the project and more generally within the scientific and industrial community focusing on space science and artificial intelligence are highly encouraged. KULeuven is aspiring to become a leader in artificial intelligence (AI) as the very recent construction of the Genius supercomputer with a dedicated partition proves. KULeuven has also several group leaders in AI and we will encourage interdisciplinary collaborations with computer scientists and engineers. The work place is Leuven, a historic university town (our university is one of the oldest in Europe, founded in 1425) located just 20 minutes from the center of Brussels and 15 minutes from Brussels international airport, making it easily reachable for international travelers. Leuven is an international city located in the Flemish (Dutch speaking) part of Belgium, where English is spoken routinely in all places (from University and public offices to shops and entertainment venues). The distance from Brussel and from other French speaking parts of the country is so small that it is perfectly possible to commute. Our division, the Center for mathematical Plasma Astrophysics (CmPA,, is a leading center in the study of space science. Our team is formed of four professors (plus one active emeritus) and about 40 experts, scientists, postdocs and students working on different aspects of simulation and data analysis applied to solar and space science, astrophysics and other plasma processes (nuclear fusion energy, industrial, space propulsion).


AIDA brings a transformational innovation to the analysis of heliophysics data in four steps.

First, AIDA will develop a new open source software called AIDApy written in Python (a free language) and capable of collecting, combining and correlating data from different space missions. AIDApy wants to replace mission-specific tools written for costly languages (such as IDL) that exclude many scientists, students and amateur space enthusiasts from exploring the data, with a much-needed single platform where methods are shared and continuously improved by the whole community.

Second, AIDA will introduce modern data assimilation, statistical methods and machine learning (ML) to heliophysics data processing. Unlike traditional methods based on human expertise, these methods rely on statistics and information theory to extract features that are hidden in the data.

Third, AIDA will combine real data from space missions with synthetic data from simulations developing a virtual satellite component for AIDApy. This feature will be demonstrated in the comparison with existing mission data and in the planning of new missions.

Fourth, AIDA will deploy in AIDApy methods of Artificial Intelligence (AI) to analyse data flows from heliophysics missions. This task requires bridging together competences in computer science and in heliophysics and pushes well beyond the current state of the art in space data analysis, connecting space researchers with AI, one of the fastest growing trends in modern science and industrial development.

AIDA will use the new AIDApy in selecting key heliophysics problems to produce a database (AIDAdb) of new high-level data products that include catalogs of features and events detected by ML and AI algorithms. Moreover, many of the AI methods developed in AIDA will themselves represent higher-level data products, for instance in the form of trained neural networks that can be stored and reused as a database of coefficients.

These tasks will be the collective responsibility of the whole consortium and certainly not of any single person. The selected candidate will work on aspects of the project best suited to her or his abilities and interests. Research freedom will be highly valued, under the guidance of the need to reach some projects goals. Reaching the goals is a task that can be done in many ways and research is finding out how to reach them. The candidate will be supported by a team of experts at KULeuven including both senior and junior research experts. The plan is to have a  stimulating collaborative environment that puts all in the position to do best what the research they like the most.


At least three, of the following items should be very familiar to the selected candidate, or the candidate should have an interest to learn in a concentrated initial effort:

  • Machine Learning, Deep Neural Networks, Bayesian Methods,

  • Data assimilation methods  (Kalman filters),

  • Solar, Magnetospheric and Solar wind data analysis,

  • Expertise on computer programming with Python, C, C++ or Fortran,

  • Knowledge of advanced parallel programing (OpenMP, MPI, CUDA)

  • Plasma physics, astrophysics or space physics,

  • Numerical methods for fluid dynamics, MHD and kinetic physics particle in cell (PIC) methods.


  • Starting: Immediately or upon availability of the selected candidate, with target date September 1, 2020. Working remotely will be possible and encouraged until the COVID19 crisis is not history. However, the buildings of KULeuven are now open regularly and it is possible to go to one’s office. 

  • Duration: 1 year, with possible extensions up to three years, depending on performance evaluation and funding.

  • Salary: the standard salary for PostDocs at KULeuven is amongst the highest in Europe. More information on the conditions at:

  • Teaching experience: There will be opportunities for teaching experiences, lecturing, supervision of student projects, guiding the candidate to develop an academic curriculum.

  • Publication: We will focus on developing open source software and peer reviewed papers.

  • Career perspective: our previous postdocs work now in academia (e.g. KTH in Sweden, CNR in Italy, EPFL in Switzerland, University of Surrey and University of Lancaster in the UK, University of Colorado and LANL in USA, University of Wuhan, China) and industry (e.g. Ubisoft Berlin, Flemish Supercomputer Centre, Royal Observatory of Belgium, Samsung, Cardiatis Belgium).


For more information please contact:

You can apply for this job no later than September 14, 2020 via the
KU Leuven seeks to foster an environment where all talents can flourish, regardless of gender, age, cultural background, nationality or impairments. If you have any questions relating to accessibility or support, please contact us at
  • Employment percentage: Voltijds
  • Location: Leuven
  • Apply before: September 14, 2020
  • Tags: Wiskunde

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