Institution: University of Paris-Est Créteil (UPEC)
Laboratory: Laboratoire Images, Signaux et Systèmes Intelligents (LiSSi)- EA-395
Supervision: Dr. HDR Alice Othmani (UPEC) & Dr. HDR. Ghazaleh Khodabandelou & Industrial Partner WasteTide.ai
Starting Date: Fall 2025 (flexible)
Duration: 3 years
Funding: Fully funded (university-industry co-financed)
Location: Paris (France) + collaboration with WasteTide (on-site)
Project Summary
We are seeking a highly motivated PhD candidate to join an interdisciplinary research project focused on developing advanced computer vision and AI solutions to improve industrial waste management.
The PhD will focus on three main research challenges:
- Robust waste recognition and segmentation in complex, real-world environments using deep learning;
- Fast identification of contaminants, such as heavy metals and toxic compounds, via multi-modal AI approaches;
- Estimation of the carbon footprint of waste to support smart recycling strategies.
This project aims to design and develop novel deep learning architectures — such as vision transformers, multimodal learning models, and self-supervised frameworks — that address the scientific and technical challenges of waste detection and classification in real-time industrial settings.
The work will be carried out in close collaboration with WasteTide, a fast-growing deeptech startup that develops AI-driven solutions for sustainable waste management. WasteTide is supported by Google Cloud’s Climate Accelerator, Techstars, and is labeled as a « Solar Impulse Efficient Solution ».
Candidate Profile
We are looking for a candidate who is passionate about research, with strong technical and analytical skills.
Required qualifications:
- Master’s degree (or equivalent) in Computer Science, Artificial Intelligence, Applied Mathematics, or a related field
- Strong programming skills (Python, PyTorch or TensorFlow)
- Solid foundation in deep learning and computer vision
- Interest in environmental applications and sustainability
Desirable skills:
- Experience with image segmentation, object detection, or multimodal learning
- Familiarity with real-time or embedded systems is a plus
- Good communication and teamwork skills
What We Offer
- A fully funded 3-year PhD in a dynamic academic–industrial setting
- A chance to contribute to applied research with tangible environmental and societal impact
- Support for conference travel, publications, and training
How to Apply
Please send the following documents in a single PDF to:
📧 alice.othmani@u-pec.fr and Ghazaleh.Khodabandelou@u-pec.fr and n@wastetide.ai
- CV
- Cover letter outlining your motivation and fit for the position
- Transcripts (Master’s degree or equivalent)
- Names and contact details of 1–2 referees
