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I-2503 - Phd in Explainable Ai for Data-driven Physiological and Behavioral Modelling of Car Drivers
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Description
**Temporary contract | 14+22+12 months | Full-time/40h | Belval**:
***:
**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.
In 2024, LIST and GOODYEAR signed the second phase of their partnership, 2024-2029, building on the outcomes of their previous collaboration and entering new technological areas as well. GOODYEAR-LIST Partnership 2.0 embraces Luxembourg's National priorities, such as Sustainability, Digital transformation and Circular economy, through the execution of six Strategic Research Programs: Data Science, Tire as a Sensor, End-of-Life Tire Valorization, Sustainable Materials for Non-Pneumatic Tires, Sustainable Materials for Next Generation of Pneumatic Tires, Structure-Process-Properties Relationships.
**How will you contribute?**:
**You will**:
- Investigate the precision and completeness of physiological data, proposing innovative and advanced solutions to handle missing data, outliers, and/or inconsistencies.
- Contribute to the project’s broader goals by integrating insights into actionable outcomes.
**Activities**:
- Conduct extensive background literature analysis, focusing on disentanglement, AI, XAI, and human-centric data analysis.
- Elaborate validation use-cases and participate in planning data collection studies under controlled conditions.
- Automate processes and explore state-of-the-art solutions for filtering, noise reduction, and kernel-based techniques.
- Present your findings at academic conferences and publish research in peer-reviewed journals.
- Write a PhD thesis in the field of AI and human-centric data analysis.
- Take part in research and training activities as part of your PhD program.
- Participate in outreach activities of LIST
**Is your profile described below? Are you our future colleague?**:
**Education**
- A Master’s degree or Engineer diploma in Computer Science, Artificial Intelligence, Data Science, Machine Learning, or a related field.
**Experience and skills**
- Strong knowledge of AI, Machine Learning, data-science (e.g., neural networks, deep learning, autoencoders, GANs, active learning, etc.);
- Knowledge of explainable AI and Knowledge Graphs with ontology (e.g., RDFS, OWL);
- Demonstrated experience with common advanced signal processing techniques (e.g. denoising autoencoders, robust PCA, wavelet transforms).
- Experience in methods to disentangle and integrate data sources (e.g., InfoGAN, β-TCVAE, TopDis / Topological Disentanglement, Independent Component Analysis (ICA), Variational Autoencoders (VAEs), and matrix factorization techniques);
- Experience with programming in Python and machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn);
- Excellent communication skills and the ability to work collaboratively in an interdisciplinary environment.
**Language skills**
- Proficiency in English (written and spoken). Knowledge of French is an asset but not mandatory.
**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
- Personalized learning programme to foster our staff’s soft and technical skills
- 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, 13-month salary, statutory health insurance
- Flexible working hours, home working policy and access to lunch vouchers
- A motivation letter oriented towards the position and detailing your experience;
- A scientific CV with contact details;
- List of publications (and patents, if applicable);
- Contact details of 2 references (optional).
**Application procedure and conditions**:
- Applications will be reviewed on an ongoing basis until the position is filled;
- The main criteria for selection will be the correspondence of the existing skills and expertise of the applicant with the requirements mentioned above.
**PhD additional conditions**:
- Supervising committee: Prof. Dr. Christoph Schommer (University of Luxembourg)
- Work loca