PhD: Automated Feature Discovery for Chemical Processes

Karlstad University; Leuven; Sur place; EUR 28 000 - 42 000; Plein temps

Résumé du poste

KU Leuven invites applications for a PhD on automated feature discovery and data-driven modelling for chemical processes. The project sits within EL4CHEM and focuses on automated feature generation, selection and model identification to build accurate, interpretable models for industrial processes.

The candidate should have a PhD-related background and be motivated to combine machine learning with chemical engineering, with opportunities for publication and collaboration with industry partners.

Qualifications

• PhD in chemical engineering, process engineering, applied mathematics, data science, computer science or a related field.
• Experience with Python and machine learning is advantageous.
• Interest in combining ML with chemical-engineering problems and interdisciplinary work.

Responsabilités

• Develop automated feature generation, feature selection and model identification methods.
• Construct reliable data-driven models for complex chemical and pharmaceutical processes.
• Evaluate methods on real industrial datasets within EL4CHEM.
• Combine ML techniques with chemical-engineering knowledge for interpretable and robust models.

Connaissances

Python

machine learning

statistical modelling

feature selection

optimisation

process modelling

interdisciplinary research

Formation

PhD in chemical engineering or related field

Outils

Python

Description du poste

KU Leuven invites applications for a PhD on automated feature discovery and data-driven modelling for chemical processes. The project sits within EL4CHEM and focuses on automated feature generation, selection and model identification to build accurate, interpretable models for industrial processes.

The candidate should have a PhD-related background and be motivated to combine machine learning with chemical engineering, with opportunities for publication and collaboration with industry partners.