Postdoc in Methods and Software for Uncertainty Quantification for Inverse Problems

torsdag 03 nov 22

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Frist 12. december 2022
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Do you want to work in an interdisciplinary research team and contribute to a novel python software package? We invite applications for a two-year postdoc with focus on further development of our python package CUQIpy and the underlying computational methods for uncertainty quantification (UQ) for inverse problems.

The position is part of the research initiative CUQI: Computational Uncertainty Quantification for Inverse problems funded by the Villum Foundation and headed by Professor Per Christian Hansen. We consider inverse problems (such as image deblurring, tomographic imaging, source reconstruction, and fault inspection) and we apply methods from Bayesian inference to determine the solution’s sensitivity to errors and inaccuracies in the data, the models, etc. We create a mathematical and computational framework that enables intuitive and extensive application of UQ techniques to a range of inverse problems in academia and industry.

Responsibilities and qualifications
You will join the developer team and play an integral role in expanding CUQIpy ( to support an even wider range of inverse problems and UQ analyses. You will interact with the CUQI team to ensure that our theory and methods are put into optimal use. Your responsibilities include:

  • Design, abstraction and implementation of Bayesian inversion methods and UQ tools.
  • Acceleration of computations by exploiting problem structure and parallelization techniques.
  • Development of high-level user interfaces for non-experts.
  • Support and training of CUQIpy users.
  • Co-supervision of MSc and PhD students.

CUQIpy is developed in a highly collaborative GitHub-centered workflow with regular programming sessions, code reviews, sprints, and hackathons. The position offers rich opportunities to build a profile in scientific software development and computational UQ for inverse problems. The ideal candidate has:

  • A strong background in computational inverse problems, Bayesian statistics and high-performance computing.
  • Excellent programming skills (ideally python) and communication skills.
  • Experience with practical applications of inverse problems and real data.

It is essential to be self-motivated and to thrive on collaboration and teamwork. Furthermore, good command of the English language is required.

Candidates must have a PhD degree or equivalent in scientific computing, computational science and engineering, applied mathematics, or equivalent academic qualifications. If you do not have your diploma at the time of application, please provide a statement from your supervisor.

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 terms of employment
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 position is a full-time position, and the period of employment is 2 years. The starting date is 1 February 2023 or shortly thereafter. The workplace is DTU Compute, Section for Scientific Computing, at DTU Lyngby Campus.

You can read more about career paths at DTU here.

Further information
Further information may be obtained from Professor Per Christian Hansen ( and Senior Researcher Jakob Sauer Jørgensen (

You can read more about DTU Compute at

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 than 12 December 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:

  • Application (cover letter)
  • CV
  • Academic Diplomas (MSc/PhD – in English)
  • List of publications
  • Links to software or other material that may be relevant

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
DTU Compute is a unique and internationally recognized academic department with 385 employees and 11 research sections spanning the science disciplines mathematics, statistics, and computer science & 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.

The section for Scientific Computing at DTU Compute performs interdisciplinary research in mathematical modeling, numerical analysis and computation methods aimed at complex and large-scale problems in science, engineering and society. It has an internationally recognized team specializing in inverse problems.

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 mission to develop and create value using science and engineering to benefit society. That mission 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.