Postdoc in Artificial Intelligence for Enhanced Sorting and Plastic Recycling

Responsibilities

Description of the research topic

The envisaged research will be part of the Horizon Europe project titled “Increasing recycled content in added-value products for a resilient and digitized circular economy” (INCREACE) (approved in the call HORIZON-CL4-2021-RESILIENCE-01). In this project KU Leuven will collaborate with in total 16 other European partners, of which companies (Philips, Erion, CABKA, Neste, Pezy Group, Plastika, Vorwerk Elektrowerke, Partners for innovation, Mirec, PAS, SAP, EGEN), research institutes (Fraunhofer IZM, Fraunhofer IVV, VITO) and other renowned universities (Maastricht University, ETH).

In this project, KU Leuven will lead a “Data-driven plastic sorting, analysis and traceability” work package. The main objective of this work package is to enable a data-driven optimization of the sorting processes and higher traceability during the pre-processing of plastic recyclates. To achieve this, more detailed data is needed on the material composition and characteristics throughout the processing steps that are commonly adopted. Therefore, sampling procedures, artificial intelligence-driven sorting, and characterisation methods to define the composition of plastic recyclates during pre-processing will be developed. By validating the developments during experiments with state-of-the-art sorting equipment constructors (Redwave and Pellenc), KU Leuven aims to establish EU broadly accepted procedures to control the consistency and quality of recyclates for specific applications. 

A small multi-disciplinary team of researchers is foreseen to work on this project at the Re- and Demanufacturing Lab of the Lifecycle Engineering group of KU Leuven. Therefore, in the context of the INCREASE project:

• You will investigate how state-of-the-art deep learning technologies can be adopted in real-time in python or C++, using TensorTR, Onnx, MXNet and/or others. 
• You will investigate the technical feasibility of integrating deep learning computer vision and data fusion technologies (e.g. RGB, NIR and 3D imaging) to distinguish different impurities from the plastics flakes and to extract valuable characteristics, such as the color and size distribution. 
• You will, in parallel with these technological developments, be responsible for setting up practical sorting and sampling experiments with the different partners of the INCREASE project to validate the developed vision technologies throughout these experiments.
• You will develop novel testing procedures, obtain novel insights based on the obtained sampling results, and learn how well-established technologies could be combined with novel AI-based sorting technologies to improve plastic recycling.

Description of the vacancy

• You are part of a multi-disciplinary research group working on the topic of Life Cycle Engineering (LCE) under the supervision of Prof. Jef Peeters.
• You follow-up literature, patents, company releases, conferences, etc., and use the obtained information to determine the state-of-the-art and identify opportunities for novel contributions to the field. 
• You are responsible for developing, implementing, and evaluating real-time running convolutional neural networks for segmentation, classification and object detection of materials on a fast running conveyor and take the lead in organizing and performing validation experiments.
• You guide Master students with their thesis work.
• You report to your senior colleagues, supervisors, and the different partners during the bi-annual project meetings organized at the premises of the different project partners
• You present your research results at international conferences.
• As a postdoc (optional) you contribute to writing project proposals and in the guiding of junior colleagues in their research and publications.

Profile

Offer

• We offer a varied and challenging job with an attractive salary package.
• We offer a research position in a stimulating and multi-disciplinary environment and a solid industrial network.
• We will support you in publishing in high-ranked international scientific journals.
• We provide the opportunity to work towards obtaining a PhD degree within an international network (optional).

Interested?

For more information please contact Prof. dr. Jef Peeters, tel.: +32 16 32 25 69, mail: jef.peeters@kuleuven.be.

In your application, please refer to Polytechnicpositions.com