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. Workplace
We offer a full‑time position for the duration of your doctoral studies, starting upon agreement with the earliest starting date of October12026. 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. 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. Benefits
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. Sustainability is a core value for us – we are consistently working towards a climate‑neutral future.
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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. Workplace
We offer a full‑time position for the duration of your doctoral studies, starting upon agreement with the earliest starting date of October12026. 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. 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. Benefits
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. Sustainability is a core value for us – we are consistently working towards a climate‑neutral future.
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PhD position in predicting Thermodynamics and Processes for Circular Carbon Plastics Arbeitgeber: Job-Room
Als Arbeitgeber bieten wir Ihnen die Möglichkeit, in einem dynamischen und innovativen Umfeld zu arbeiten, das Teamarbeit und Eigenverantwortung fördert. Unsere Unternehmenskultur legt großen Wert auf kontinuierliche Weiterbildung und persönliche Entwicklung, sodass Sie Ihre Fähigkeiten als MuleSoft Integration Engineer stetig erweitern können. Zudem profitieren Sie von flexiblen Arbeitszeiten und einer modernen Arbeitsumgebung, die Kreativität und ergebnisorientiertes Arbeiten unterstützt.
