PhD Scholarship in Digital Transformation of Catalyst Manufacturing powered by AI

Updated: about 1 month ago
Job Type: FullTime
Deadline: 10 Jul 2020

The Department of Mechanical Engineering  (DTU Mechanical Engineering) of the Technical University of Denmark (DTU) has an open PhD position in the field of “IN Digital transformation of catalyst manufacturing powered by AI”.  

The PhD will be working in the framework of the national project MADE FAST funded by the Innovation Fund Denmark. The MADE FAST project is a major national initiative comprising a network of 50 companies, 5 universities and 3 research institutes in Denmark pursuing the goals of Industry4.0. The PhD scholarship is placed in the context of the Work Stream 4 “Digitalization of Manufacturing Processes” which includes 11 PhD students working on related projects and offers unique opportunities with respect to high level training in a multinational and multicultural environment. The PhD project will be carried out in an exciting combination of academic and industrial environments. The main industrial collaboration partners are Topsøe and LEGO. 

Responsibilities and tasks  

The overall theme of the PhD project is to promote the digital transformation of the process chain in catalysts manufacturing. This chain entails several steps including mixing of reacting ingredients into a slurry (paste) as well as a subsequent extrusion process from which catalysts extrudates are produced. The PhD project evolves around three themes regarding this chain: (i) Collecting and handling data from real catalyst production lines, (ii) performing data analytics on this data with proper methods including machine learning, deep learning and process simulation models based on first-principles (iii) deploying the models in production line and coupling with control strategies  to support implementation. The ultimate goal is to develop AI-models that will be used to optimize the production process via on-line monitoring as well as feed-back and control, thus paving the way for data-based decision making. 

The PhD project will be carried out in close collaboration with Topsøe. 

The position encompasses both experimental work on sensor selection, implementation and data acquisition as well as theoretical work including machine learning and model development. 


Candidates should have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree.  

Candidates with a relevant master's degree in mechanical, chemical or manufacturing engineering, physics or applied mathematics as well as computer science are encouraged to apply. Good knowledge of production engineering technologies, instrumentation, automation, rheology, process simulation or machine learning is considered an advantage. Moreover, the candidate should have good mathematical/analytical skills as well as good communication skills. 


To apply, please read the full job advertisement at    

Application deadline: 10 July 2020. 

Technology for people 

DTU develops technology for people. With our international elite research and study programmes, we are helping to create a better world and to solve the global challenges formulated in the UN’s 17 Sustainable Development Goals. Hans Christian Ørsted founded DTU in 1829 with a clear vision to develop and create value using science and engineering to benefit society. That vision lives on today. DTU has 11,500 students and 6,000 employees. We work in an international atmosphere and have an inclusive, evolving, and informal working environment. Our main campus is in Kgs. Lyngby north of Copenhagen and we have campuses in Roskilde and Ballerup and in Sisimiut in Greenland. 

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