Internship contract | Belval | 6 Months
Are you passionate about research? So are we! Come and join us
The Luxembourg Institute of Science and Technology (LIST) is a Research and Technology Organization (RTO) active in the fields of materials, environment and IT. By transforming scientific knowledge into technologies, smart data and tools, LIST empowers citizens in their choices, public authorities in their decisions and businesses in their strategies.
Do you want to know more about LIST? Check our website: https://www.list.lu/
How will you contribute?
Interpreting random forest models is a critical challenge in applied machine learning. Recent work has shown that the structure of a random forest can be encoded as a feature graph - a network where nodes represent input variables and edges capture co-occurrence patterns along decision paths. While this representation is promising, no systematic study has examined how such graphs should be visualized to support the analytical tasks of data scientists and domain experts. This internship conducts a structured design study addressing this gap. Starting from a working implementation of the feature graph construction pipeline, the student will conduct a task analysis with domain experts to identify the key analytical questions these graphs must answer. Based on this analysis, the student will design, implement, and comparatively evaluate multiple visual representations—including node-link diagrams with centrality-based encodings, adjacency matrices, and layered representations by tree depth. A lightweight user study with data science practitioners will be conducted to assess the effectiveness and usability of the proposed designs. The results will directly inform the design of a full visual analytics system and will be submitted as a short paper to a top visualization venue (EuroVis or IEEE VIS).
You will be mainly in charge of:
- Task analysis methodology and structured design study protocol
- Implementation of a feature graph construction pipeline from scikit-learn Random Forest models
- Design and prototyping of interactive graph visualizations (D3.js or equivalent)
- Comparative evaluation of visual representations across datasets of varying dimensionality
- Lightweight user study design and qualitative analysis
- Scientific writing targeting a short paper in a top visualization conference
You will be closely mentored by, and work alongside, researchers active in the visualization (VIS) research community, giving you direct access to state-of-the-art knowledge and hands-on training in visual analytics and machine learning interpretability.
Is your profile described below? Are you our future trainee? Apply now!
Education
- Final year in Master of Science in Computer Science, Engineering, Data Science or equivalent.
- Proficient in a modern programming language such as Python, Java or similar.
- Proficient in Frontend development languages (Javascript, HTML, CSS).
- Familiarity with a data visualization library, D3js is a plus.
- Familiar with machine learning methods, especially Decision Trees or Random Forests.
- Ability to understand scientific and technical documents and reimplement their ideas.
Language skills
- Fluency in English (and French), both oral and written. Other relevant languages are an asset.
Your LIST benefits
- An organization with a passion for impact and strong RDI partnerships in Luxembourg and Europe that works on responsible and independent research projects
- Sustainable by design, empowering our belief that we play an essential role in paving the way to a green society
- Innovative infrastructures and exceptional labs occupying more than 5,000 square metres, including innovations in all that we do
- An environment encouraging curiosity, innovation and entrepreneurship in all areas
- Multicultural and international work environment with more than 50 nationalities represented in our workforce
- Diverse and inclusive work environment empowering our people to fulfil their personal and professional ambitions
- Gender-friendly environment with multiple actions to attract, develop and retain women in science
- 32 days’ paid annual leave, 11 public holidays
The monthly gross internship allowance is 1,400 euros for a full-time equivalent (40 hours per week).
Apply online
Your application must include:
- A CV with contact details
- A motivation letter oriented towards the position and detailing your experience
Please apply ONLINE formally through the HR system. Applications by email will not be considered.
Application procedure and conditions
We kindly request applicants to provide their nationality for statistical purposes only, as part of our commitment to promoting diversity and ensuring equal opportunities in our workforce. This information will be kept confidential and will not be used for any discriminatory purposes.
LIST is dedicated to maintaining an inclusive work environment and is an equal opportunity employer. We are committed to attracting, hiring, and retaining a diverse workforce. All applicants will be considered for employment without discrimination based on national origin, race, colour, gender, sexual orientation, gender identity, marital status, religion, age, or disability.
Applications will be continuously reviewed until the position is filled. An assessment committee will thoroughly evaluate applications, adhering to guidelines designed to ensure equal opportunities. The primary criteria for selection will be the alignment of the applicant's existing skills and expertise with the requirements mentioned above.
As part of our recruitment process, the selected candidate might be subject to a background check in accordance with applicable laws and institutional policies. Further checks and restrictions might apply to candidates in compliance with export controls requirements
For the purposes of the position and in accordance with applicable legislation, the successful candidate may be requested to provide a recent criminal record certificate.
Languages English Education Master