PhD: Predictive Thermodynamics for Circular Plastics

Emerging Scholars Council; Zürich; Vor Ort; CHF 60.000 - 80.000; Vollzeit

Zusammenfassung

ETH Zurich's Energy and Process Systems Engineering (EPSE) Group seeks a doctoral student to develop predictive models for complex fluids and solvent-based plastics recycling. The project links machine learning with thermodynamics, backed by a funded ERC Advanced Grant DISC3Lab.

The role includes mentoring, collaboration with experimental teams, and dissemination through publications and conferences, starting around October 2026.

Qualifikationen

• Excellent Master's or diploma in chemical engineering, process engineering, mechanical engineering, energy science & technology, physical chemistry, or related field.
• Experience with ML methods to predict thermophysical properties or process design is desirable.
• Strong written and oral English skills.

Aufgaben

• Advance thermodynamically consistent prediction methods for fluid properties or separation processes.
• Develop hybrid thermodynamic and data-driven predictive models to address data sparsity and uncertainty.
• Collaborate with experimental colleagues and co-supervise student projects.
• Publish results in peer‑reviewed journals and present at international conferences.

Kenntnisse

English language proficiency

Communication skills

Independent work

Ausbildung

Master's or diploma in chemical engineering or related field

Tools

ML techniques

Jobbeschreibung

ETH Zurich's Energy and Process Systems Engineering (EPSE) Group seeks a doctoral student to develop predictive models for complex fluids and solvent-based plastics recycling. The project links machine learning with thermodynamics, backed by a funded ERC Advanced Grant DISC3Lab.

The role includes mentoring, collaboration with experimental teams, and dissemination through publications and conferences, starting around October 2026.