PhD Project in Deep Learning for Segmenting and Characterizing 3D Microstructure

Department of Applied Mathematics and Computer Science’s (DTU Compute) section for Visual Computing, would like to invite applications for a 3-year PhD position starting 1 October 2021. The project is financed by Innovation Fund Denmark. If you are interested in deep learning, 3D image analysis, computer vision, and experimental work, this PhD position could be exactly what you are looking for.

DTU Compute at Technical University of Denmark encompasses both in-depth theory and practical applications, across disciplines. We build models, perform calculations, and run simulations, relating results back to the real world to solve problems. This project will be part of the Section for Visual Computing at DTU Compute which is an international research group consisting of around 40 researchers (faculty: 10, PhDs/postdocs: 30). The section is an active part of the 3D Imaging Center at DTU, includes an ImageLab with vision systems for acquiring shape and reflectance, has access to the DTU Computing Center, and has a long history of interdisciplinary projects in collaboration with academic and industrial partners. 

Project Description
This position is part of a research project on real-time monitoring of continuous mozzarella production, where you will be part of a large research team. Your role will be to find methods for segmenting and characterizing the physical microstructure of materials. More specifically, you will perform the CT scans of cheese on local instrumentation and work on methods for characterizing the filament structure and other structures of mozzarella cheese from 3D µCT images and correlating these with functional cheese properties. Results from your research will be used by another PhD student who investigates models for relating optical properties and structure of mozzarella. Instrumentation and inline use of methods will be done by a vision company associated with the project. You are expected to research how to segment structures in 3D from CT images and how these structures relate to functional properties. Segmentation will be done using deep learning and similar methods, and the results which you obtain will be practically used for determining the optical properties.

Responsibilities and tasks
Your overall focus will be 3D image analysis for characterizing and modelling microstructure. To accomplish this, you will perform CT scans and create methods for segmenting fibrous structures in 3D µCT images and make appropriate data structures to represent the segmented objects. This will take an offset in deep learning-based segmentation methods. You will be part of a research project encompassing both nearby colleagues and external academic and industrial partners.

Your primary tasks will be to:

• Estimate structural properties from 3D µCT images.
• Develop models for quantifying changes in microstructure.
• Relate structural properties to functional properties
• Perform µCT scannings of mozzarella samples.
• Collaborate with another PhD student for extraction of structural properties most important for optical appearance
• Write scientific papers and present research results at conferences.
• Work as a teaching assistant in two or three 5 ECTS modules.

Qualifications
You 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. The master degree should be in Computational Science and Engineering (CSE), Applied Mathematics, Physics,  Engineering or equivalent. 

Technical Proficiency

• Solid background in image analysis.
• Experience with deep learning.
• Foundations in calculus, programming, physics, and geometric modelling.
• Interest in practical experiments
• Some experience with CT is preferred, but is not a requirement

Soft Skills Requirements

• Fluent spoken and written English. Minimum proficiency level is B2, C1 is preferred.
• Self-reliant working style
• Curious and ambitious personality.
• Prior research and publication experience is considered a definite plus but is not required.

Approval and Enrolment
The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in the DTU Compute PhD School Programme. For information about the general requirements for enrolment and the general planning of the PhD study programme, please see the DTU PhD Guide. 

Assessment

The assessment of the applicants will be made by Associate Professor Anders Nymark Christensen and Professor Anders Bjorholm Dahl.

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 position is a full-time position. The period of employment is 3 years starting 1 October (or as soon as possible thereafter).

You can read more about career paths at DTU here.

Further Information
Further information concerning the project can be obtained from Associate Professor Anders Nymark Christensen, anym@dtu.dk, Phone: +45 4525 5258.

Further information concerning the application is available at the DTU Compute PhD homepage.

If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU – Moving to Denmark.

Application
Your complete online application must be submitted no later than 1 August 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
• Grade transcripts and BSc/MSc diploma
• Excel sheet with translation of grades to the Danish grading system (see guidelines and Excel spreadsheet here)

You may apply prior to ob­tai­ning your master's degree but cannot begin before having received it.

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. DTU has campuses in all parts of Denmark and in Greenland, and we collaborate with the best universities around the world.