PhD Scholarships in Mathematical Modelling, Simulation, Control and Optimization (Advanced Process Control and Model Predictive Control) for the Electrification of Industrial Processes using Renewable Energy Sources

torsdag 23 jun 22

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Frist 8. juli 2022
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In these PhD projects you develop new methods and algorithms for advanced process control and model predictive control for industrial processes with zero climate gas emission and based on renewable electrical energy. This will give you the opportunity to participate in pioneering research activities developing control systems for novel large-scale industrial processes.

To eliminate climate gas emission from industrial processes such as fuel, chemical and cement production, these manufacturing processes, and their operation must be redesigned such that they can utilize electricity from renewable energy sources such as solar and wind power. The operation of such processes with significant intermittent power production and with storage systems requires new advances control systems based on forecasting and optimization that can efficiently and robustly coordinate the power production, storage, and consumption. Also, the operation of the industrial processes consuming electrical power must be redesigned such that it operates in coordination with the power system. The industrial electrical consumption processes that we consider in the projects include water electrolysis, air separation, ammonia production, and methanol production as well as thermal storage in combination with novel processes for cement production. You will develop mathematical models for these systems, simulate them using high-performance scientific computing, and develop online control and optimization systems that you will simulate in closed loop. You will also test the resulting systems in pilot plants and industrial plants with our industrial partners.

In the projects we develop new advanced process control systems and model predictive controllers for electrification of industrial processes. Novel numerical methods and modelling and real-time control systems will be developed to facilitate operation of electrified industrial processes.  We test these systems by simulation using mathematical models and simulators that we develop in the projects. We also test the advanced process control systems and model predictive controllers for real plants in collaboration with our industrial partners.

The work is conducted as part of large research consortia with academic and industrial partners. You will be part of this network and participate in project meetings, workshops and conferences.The positions will be associated with the EcoClay and NewCement projects that concerns development of CO2 emission free cement production as well as the DynFlex project that concerns flexible operation of Power-to-X (X = H2, NH3, CH3OH) plants. In these projects, we develop systems for advanced process control based on forecasting and optimization.

Responsibilities and qualifications
You will develop new advanced process control systems based on forecasting and optimization algorithms for electrification of industrial processes and their flexible dynamical operation. To do this you will develop mathematical models that describe the electrical systems and the industrial processes.

You will develop and implement

  • numerical methods for simulation of dynamical systems (ordinary differential equations differential algebraic equations, partial differential equations, stochastic differential equations)
  • optimization of dynamical systems
  • state and parameter estimation of dynamical systems for predictions and forecasting
  • model-based experimental design for dynamical systems
  • methods for uncertainty quantification by closed-loop simulation
  • You will also be involved in teaching and supervision of BSc and MSc students
  • Participate in conferences, write papers and a PhD thesis

You must have strong skills in computational methods for systems and control, scientific computing, model predictive control, optimization, and time series analysis (forecasting). It is desirable if you have experience with state estimation and control based on stochastic differential equations. You must be able to demonstrate experience with mathematical modeling.

It is also a requirement that you can program and have some experience with C/C++ as well as  Matlab/Octave, Python or Julia.  We expect that you know high-performance computing and have experience with the Linux operating system for high-performance scientific and technical computing. Strong computer science skills for (soft) real-time systems, databases, parsing and compiler construction will also be highly desirable.

In addition, it is desirable with knowledge about computational thermodynamics, transport processes, process control, and mathematical modeling of chemical processes. In particular, prior experience with modeling of electrolysis, chemical reactors (ammonia and methanol), and cement processes will be desirable. 

The projects are inter-disciplinary, and you must be able to collaborate and work efficiently with stakeholders from industry and other academic departments. Therefore, you must have strong collaboration and interpersonal skills to succeed.  

You must 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.

Approval and Enrolment
The scholarships for the PhD degree are subject to academic approval, and the candidates will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education.

Assessment
The assessment will be conducted by Professor John Bagterp Jørgensen.

We offer
DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility.

Salary and appointment terms
The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union. The period of employment is 3 years. The starting date is September 1, 2022 or as soon as possible according to mutual agreement. The positions are full time positions.

You can read more about career paths at DTU here.  

Further information
Further information may be obtained from Professor John Bagterp Jørgensen (E-mail: jbjo@dtu.dk). 


You can read more about DTU Compute at www.compute.dtu.dk

If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU – Moving to Denmark. Furthermore, you have the option of joining our monthly free seminar “PhD relocation to Denmark and startup “Zoom” seminar” for all questions regarding the practical matters of moving to Denmark and working as a PhD at DTU.

Application procedure
Your complete online application must be submitted no later than 8 July 2022 (Danish time). Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link "Apply online", fill out the online application form, and attach all your materials in English in one PDF file. The file must include:

  • A letter motivating the application (cover letter)
  • Curriculum vitae
  • Grade transcripts and BSc/MSc diploma (in English) including official description of grading scale
  • A list of publications (it can be part of the CV)

Incomplete applications will not be considered. You may apply prior to ob­tai­ning your master's degree but cannot begin before having received it.

Applications received after the deadline will not be considered.

All interested candidates irrespective of age, gender, disability, race, religion or ethnic background are encouraged to apply.

DTU Compute
The positions are in the Scientific Computing section at DTU Compute. DTU Compute is the largest department in applied mathematics and computer science in Denmark and conduct research and education within applied mathematics, statistics, and computer science. The Scientific Computing section do research in computational methods for the technical sciences. You will be attached to the Model Predictive Control group in the section for Scientific Computing and be part of internationally leading research in Model Predictive Control for industrial processes, energy systems, and biomedical systems. You will also collaborate with DYNSYS at DTU Compute. DYNSYS are world leading experts in forecasting and prognosis for energy systems.

DTU Compute is a unique and internationally recognized academic department with 385 employees and 11 research sections spanning the science disciplines mathematics, statistics, computer science, and engineering. We conduct research, teaching and innovation of high international standard – producing new knowledge and technology-based solutions to societal challenges. We have a long-term involvement in applied and interdisciplinary research, big data and data science, artificial intelligence (AI), internet of things (IoT), smart and secure societies, smart manufacturing, and life science. At DTU Compute we believe in a diverse workplace with a flexible work-life balance.

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 13,400 students and 5,800 employees. We work in an international atmosphere and have an inclusive, evolving, and informal working environment. DTU has campuses in all parts of Denmark and in Greenland, and we collaborate with the best universities around the world.