PhD position in predicting Thermodynamics and Processes for Circular Carbon 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

The Energy and Process Systems Engineering (EPSE) Group at ETH Zürich is looking for a doctoral student to work on the new generation of prediction methods for the complex fluids and separation processes involved in the solvent-based recycling of plastics.

The EPSE group, led by Prof. Dr. André Bardow, is dedicated to advancing sustainable energy and chemical process systems. Our research spans from the molecular level to the scale of systems. We develop simulation and experimental methods to advance sustainable energy and chemical processes from the molecular to the system scale.

Project background

The vision of our recently funded ERC Advanced Grant DISC3Lab is to devise a validated discovery loop for sustainable chemical processes, targeting the solvent-based recycling of plastics. Chemical recycling is a key element of a transition towards a chemical industry within the Planetary Boundaries. However, the current process design paradigm is too slow, labor-intensive, and fragmented between disciplines.

We aim to overcome these bottlenecks to accelerate the development of sustainable processes. For this purpose, this project will develop predictive models, ranging from the basis in thermodynamic mixture properties to conceptual process design for chemical plastics recycling, by linking advanced machine learning techniques with high‑throughput experimental methods developed by other team members.

Job Description

• Your main task will be to advance thermodynamically consistent prediction methods for fluid properties and/or separation processes by developing new, more general, and more reliable hybrid thermodynamic and data-driven predictive models


• The methods developed in this project will overcome current limitations in training data sparsity, quantification of model uncertainty, and poorly specified mixtures or separation processes


• The work will be conducted in tight integration with a companion doctoral candidate who will focus on advancing the experimental counterpart methods


• Your role will also involve mentoring and co-supervising student projects and theses


• Additionally, you will engage in various group and institute duties and activities


• As an integral part of your work, you will publish your results in peer‑reviewed journals and present them at international conferences

Profile

• You meet the requirements for a doctoral program at ETH Zurich and have an excellent Master's or diploma in chemical engineering, process engineering, mechanical engineering, energy science & technology, physical chemistry, or a related field


• Ideally, you already have experience in ML and methods to predict thermophysical properties and/or conceptual process design


• The ability to work independently and excellent communication and writing skills in English complete your profile

We offer

We offer a full‑time position for the duration of your doctoral studies, starting upon agreement with the earliest starting date of October 1st, 2026. We are providing a supportive environment that fosters professional and personal growth. You will join a dynamic, motivated, and interdisciplinary team of researchers with expertise in thermodynamics, process design, energy system optimization, and life cycle assessment, working collaboratively with research and industry partners. You will work in an inspiring, collaborative environment to address critical global challenges. It includes opportunities to engage in group discussions and collaborative efforts spanning from the molecular level to the systems scale, offering insights into diverse methods and approaches.

The PhD position provides access to state‑of‑the‑art laboratory facilities and experimental setups, enabling impactful research. The position supports the development of critical thinking, data analysis, problem‑solving, and project management skills while contributing to the broader academic community through publications and presentations at leading conferences.

Working, teaching and research at ETH Zurich

We value diversity and sustainability

In line with our values, ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and Diversity website to find out how we ensure a fair and open environment that allows everyone to grow and flourish. Sustainability is a core value for us – we are consistently working towards a climate‑neutral future.

For further information about the Energy and Process Systems Engineering (EPSE) Group, please visit our website. Questions regarding the position should be directed to Dr. Emiliano Casati [email protected] or [email protected] (no applications).

About ETH Zürich

ETH Zurich is one of the world’s leading universities specialising in science and technology. We are renowned for our excellent education, cutting‑edge fundamental research and direct transfer of new knowledge into society. Over 30,000 people from more than 120 countries find our university to be a place that promotes independent thinking and an environment that inspires excellence. Located in the heart of Europe, yet forging connections all over the world, we work together to develop solutions for the global challenges of today and tomorrow.