Postdoc in Model Based Control

Updated: 19 days ago

The section for Scientific Computing at DTU Compute offers a 2 year Post Doc position in Model Based Control. The position is available as soon as possible and ideally from June 1, 2021. The candidate in this post doc position must combine systems and control with high-performance scientific computing and mathematical modeling to develop novel numerical algorithms and systems for model based control. In particular, you should contribute to the development mathematical models, simulation, and model based control systems within medicine and medical devices. The position requires collaboration with other researchers at universities, in hospitals and in industry as well as supervision of students and dissemination of results in scientific journals. 

Project Description
In this project, we develop model based control algorithms for cyber-physical systems with applications in medicine and technology. In particular, we will have a focus on applications related to diabetes and metabolism in man. We develop numerical algorithms tailored for real-time control systems for embedded applications that can be used in medical devices and other engineering systems. The ambition is to establish a new platform for agile implementation of model based control and cyber-physical systems. You will have an important role in development and implementation of computationally efficient algorithms from scientific computing as well as systems and control for optimization and model based control systems as well as participation in the overall cyber-physical system. The ambition is to develop a new standard of computational methods for systems and control (in particular model predictive control) that is demonstrated in cyber-medical and cyber-physical systems.

Responsibilities and tasks
Your tasks and responsibilities are to develop high-performance algorithms for model based control and cyber-physical systems. This involves that you

  • Develop, implement and test new numerical algorithms for nonlinear model predictive control in embedded systems
  • Develop algorithms for numerical simulation that can run in embedded systems and well as in high-performance computing environments.
  • Develop algorithms and systems for uncertainty quantification for closed-loop systems
  • Develop mathematical models for metabolism in man
  • Implement a cyber-physical system based on advanced process control
  • Do research and development within numerical algorithms, scientific computing and computer science for cyber-physical systems with applications in engineering, science and medicine
  • Publish the results in journal papers
  • Participate in practical verification of the developed systems
  • Advise B.Sc., M.Sc., and PhD students
  • Write applications for further funding of research projects related to model based control

You must have an interest in development of new algorithms, implementation of new algorithms, application of these algorithms, and dissemination of such algorithms and applications in journal papers. 

Qualifications
You must have a MSc degree and a PhD degree in Applied Mathematics with a strong focus on scientific computing and optimization based control. We expect that you have a strong profile with significant international experience in computational methods for systems and control. You must have a strong documented track record in developing model based control systems based on high-performance scientific computing. We expect that you have experience from industry with development of MPC algorithms and also previous international experience from a post doc position. You must be able to document previous experience with development of model-based optimization and control algorithms in C/C++ as well as in Matlab. Proficient knowledge of Linux and Unix-based tools for high-performance computing is required. Knowledge about industrial model predictive control systems and their implementation in C# would be considered an advantage. In addition, we expect the following qualifications:

  • Documented knowledge of nonlinear model predictive control based on stochastic differential equations
  • Experience with nonlinear MPC for reacting systems and mathematical modeling of such systems
  • Strong programming skills in C/C++ and Matlab
  • Knowledge of Python, Julia, Fortran and other tools for scientific computing is an advantage.
  • Extensive experience with scientific publications about dynamic optimization, optimal control and topics related to model predictive control
  • Fluent in spoken and written English.
  • Self-reliant working style but with strong interpersonal skills and an ability to collaborate with other researchers at universities, hospitals, and in industry.
  • Curious and ambitious personality with an ambition for a career in academia.

Assessment
The assessment of the applicants will be made 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 2 years.  

You can read more about career paths at DTU here . 

Further information
Further information may be obtained from John Bagterp Jørgensen, email: 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

Application procedure
Your complete online application must be submitted no later thanTuesday 25 May 2021 (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
  • Diploma (PhD and MSc)
  • List of publications
  • Copy/list of 10 peer-reviewed publications that are relevant to dynamic optimization, optimal control, and NMPC and where you are the main author

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

DTU Compute
DTU Compute is a unique and internationally recognized academic environment 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.

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 12,900 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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