PhD Research in Machine Learning University

Mechanical recycling of plastics is the most efficient way to treat plastic waste sustainably. However, the quality of recyclates is usually compromised, leading to products with inferior properties. The quality of reprocessed samples (recyclates) depends on many factors and is also application-dependent. An effective recycling process benefits from products with low variability in properties such as rheological and mechanical characteristics. To achieve this, several tests are required, and a sorting and recycling line needs to be optimized to predict the quality of the output.

The predictions should be carried out in a scientifically and economically viable method to assure applicability in the industry.

Qualifications

• Polymer-oriented materials scientist/engineer with a background in data science. A distinct track record in at least one of these polymer groups is required: packaging polymers like polyolefins and/or PET, or technical polymers like ABS, PC, and (HI)
  PS. A background in textiles engineering or rubbers does not meet these requirements.
• Experience with polymer processing machinery such as injection moulding and extrusion.
• Experience with polymer characterization methods such as tensile, impact, rheology, IR, Raman, and HDT is required.