PhD position: Machine Learning for Sustainable Chemicals and Processes
vor 1 Woche
Job description
This Ph.D. position is located at the frontier of sustainable chemicals research, combining process systems engineering with machine learning methods. You will contribute to early-stage technology development for chemicals and plastics by leveraging recent advances in machine learning to develop predictive methods for process design and life cycle assessment. You will investigate novel technologies developed by our partners within NCCR Catalysis and its strong network of industrial partners and consider the transition of the whole chemical industry from a systems perspective. This multifaceted approach offers a unique opportunity to deepen your understanding of sustainable chemicals, engage in environmental assessments and optimization, and collaborate with industry and academia partners for successful project outcomes.
We offer you a full-time position for the duration of your doctoral studies, starting upon agreement with the earliest starting of 1 October . You will work in an interdisciplinary team of researchers with in-depth experience in process design, machine learning, and life cycle assessment. As an integral partof your work, you will publish your results in peer-reviewed journals and present them at international conferences.
Profile
We are looking for a proactive and motivated candidate who meets the requirements for a doctoral program at ETH Zurich and has a Master's or diploma degree in chemical engineering, mechanical engineering, process engineering, energy science & technology or similar programs from a recognized university. Ideally, you already have experience in conceptual process design, machine learning, life cycle assessment and programming. You are highly motivated to learn and apply modern simulation and optimization techniques and work in a dynamic environment with other doctoral students and postdocs. The ability to work independently and excellent communication skills in English (both written and spoken) complete your profile.
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