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Postdoc in Deep Learning for 3D Image Analysis – DTU Compute, Denmark, 2022


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Postdoc position is available in Deep Learning for 3D Image Analysis at DTU Compute, Denmark, 2022

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General Info

Position: Postdoc
No. of Positions: 1
Research Field:
Joining Date: ASAP
Contract Period: 2 Years
Salary: Subject to norms

DTU Compute
DTU, Kgs. Lyngby, Denmark

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Qualification Details

We expect that you have a background in image analysis machine learning and have experience with

  • deep learning for analyzing images for example in computer vision, medical, or materials applications,
  • non-learning methods for image analysis, and
  • analyzing image data at a large scale.

It will also be an advantage if you are experienced with using distributed high-performance computing systems and experience with the analysis of 3D images from synchrotron or lab X-ray CT.

As a formal qualification, you must hold a PhD degree (or equivalent).

Responsibilities/Job Description

Your focus will be on research in deep learning methods for 3D large-scale imaging, i.e. images that are 10-100 times larger than typical medical CT images. Deep learning has significantly impacted computer vision and gained much popularity in the medical domain, but for large-scale 3D imaging, deep learning is less employed. Despite deep learning methods are not widely used, they have great potential and especially if we can incorporate prior knowledge.

In this project, we will focus on methods that can incorporate morphology (shape) and topology (connectivity) as part of the learning. Your work will focus on developing deep learning methods applied to 3D images acquired by our collaborators at Aarhus University in the Interdisciplinary Nanoscience Center. In Aarhus, there will be another postdoc working on this project. The scientific questions will involve for example vascular and lacuno-canalicular networks in bone. Other composite materials may also be included. This position is in the Visual Computing Section at DTU, where there is a large research group focusing on image analysis methods for 3D imaging.

How to Apply?

Application Method: Online Application
Ref. No.: -

Application Procedure

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

About the Department/Section/Group

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

About the Employer: Technical University of Denmark (DTU), Denmark

Note or Other details

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 two years.

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.

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Contact details

Further information may be obtained from Anders Bjorholm Dahl, e-mail: [email protected], Phone: +45 5189 6913.

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Published on: | Last Updated: Nov 19, 2022 | at nViews Career by nViews Career Team