Postdoc position in physics-informed ML
3 weeks ago
The over-arching goal is to expedite the capability to tackle the time-critical sustainability challenges by leveraging machine learning / artificial intelligence tools, which can not only provide mechanistic understanding but also enhance predictive capability of the green engineering processes. About the research The research topic is in Chemical Process Engineering. One crucial challenge is to develop and design novel processes for the manufacturing of chemicals, materials and fuels from renewable sources. Many other important sustainability-related needs include recycling, process intensification, more energy efficient processes, etc. In all these applications, there will be a number of different reactors and separation equipment, many of them quite different compared to the present process industry. Consequently, fundamental understanding of unit operations, such as separation (mixing, distillation, drying, filtration, etc) and mass/heat transfer, is important. This calls for innovative experimentation on the laboratory scale combined with mathematical modeling. We aim to forge new alliances and open up new collaborations to address current and forthcoming applications of relevance to society and industry. In this process, there is also a need to maintain a proper balance between fundamental and applied research within the area. Such a continued strategic development of Chemical Process Engineering research at Chalmers has the potential to significantly contribute to the realization our overall vision for a sustainable future. Major responsibilities The project will focus on developing physics-informed machine learning / artificial intelligence models for chemical engineering unit operations / processes. The key responsibility as postdoc is to independently drive the research to bridge gaps in the knowledge base. The position will involve reporting current research results in both written and oral forms, as well as authoring scientific research publications. The position may also include teaching on undergraduate and master's levels as well as supervising master's and/or PhD students to a certain extent. Another important aspect involves collaboration within academia and with society at large. The position is meritorious for future research duties within academia as well as industry/the public sector. Qualifications You should have, or expect to soon obtain, a PhD degree in Chemical Engineering or a related subject area. Experience with machine learning / artificial intelligence modeling is required. To qualify for the position of postdoc, you must hold a doctoral degree awarded no more than three years prior to the application deadline (according to the current agreement with the Swedish Agency for Government Employers). Exceptions from the 3-year limit can be made for longer periods resulting from parental leave, sick leave or military service*. The position requires sound verbal and written communication skills in English. Swedish is not a requirement but Chalmers offers Swedish courses. You are expected to be somewhat accustomed to teaching, and to demonstrate good potential within research and education. * The date shown in your doctoral degree certificate is the date we use, as this is the date you have met all requirements for the doctoral degree. Contract terms This postdoc position is a full-time temporary employment for two years. We offer Chalmers offers a cultivating and inspiring working environment in the coastal city of Gothenburg. Read more about working at Chalmers and our benefits for employees. Chalmers aims to actively improve our gender balance. We work broadly with equality projects, for example the GENIE Initiative on gender equality for excellence. Equality and diversity are substantial foundations in all activities at Chalmers. Application procedure The application should be marked with 20240188 and written in English. The application should be sent electronically and be attached as PDF-files, as below. Maximum size for each file is 40 MB. Please note that the system does not support Zip files. CV: (Please name the document as: CV, Surname, Ref. number) including:
- CV, include complete list of publications
- Previous teaching and pedagogical experiences
- Two references that we can contact.
- Introduce yourself
- Describe your previous research fields and main research results
- Describe your future goals and future research focus
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