BEMÆRK: Ansøgningsfristen er overskredet
We have two open Ph.D. positions in AI driven medical image analysis. If you would like to be part of a multidisciplinary research group that aims at using AI methods to reduce the risk of stroke or cardiac death then this position could be your chance.
The projects are focused on deep learning based methods on 3D CT for cardiovascular risk prediction in collaboration with the heart center at Rigshospitalet. From the computational side, our main research interests are 3D data representations (meshes, implicit descriptions and other descriptors), latent space manipulations (deep metric learning etc), geometric deep learning and deep reinforcement learning. From the clinical side, we aim at discovering new or unexplored image biomarkers that can add to the existing patient stratification for major cardiovascular diseases. In addition to our offices at DTU Compute, we have an office and access to GPU computers at the hospital where we can work on the large databases of CT scans they have there.
Responsibilities and qualifications
Your overall focus will be to work in close collaboration with AI researches at DTU Compute and medical professionals at Rigshospitalet. You will drive the research in exploring and using new AI driven methods for discovering weakly used or unknown image biomarkers for cardiovascular risk prediction. These projects have a special focus on predicting stroke and cardiac death.
You main responsibilities will be:
- Teach and supervise BSc and MSc student projects, and be co-supervisor for PhD students
- Be a daily part of the scientific environment at DTU Compute and Rigshospitalet
- Drive research within AI driven 3D medical image analysis
- Write and publish scientific papers in technical conferences and journals
We imagine that you have:
- Strong background in deep learning and machine learning
- Knowledge of handling and visualizing large 3D images with for example ITK or Simple ITK
- Practical experience with handling 3D meshes using for example VTK or similar toolkits
- Strong Python programming background
- Strong statistical background
- Excellent English writing skills
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.
- Position 1: Ph.D. position in AI driven medical image analysis for stroke risk prediction
- Position 2: Ph.D. position in AI driven medical image analysis for cardiac death prediction
We imagine that the computational research are similar for both project and there will be a close collaboration between the Ph. D. students. While it is not mandatory, you can indicate which of the two topics that you find most interesting.
Applicable for all scholarships
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 done by Professor Rasmus R. Paulsen.
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 of the positions are fixed to 1 March 2024 due to grant restrictions.
You can read more about career paths at DTU here http://www.dtu.dk/english/about/job-and-career/working-at-dtu/career-paths.
Further information
Further information may be obtained from Professor Rasmus Reinhold Paulsen, rapa@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 15 November 2023 (23:59 Danish time)
. Applications must be submitted as one PDF file
containing all materials to be given consideration. To apply, please open the link "Apply now", 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
- List of publications
In the field “Please indicate which position(s) you would like to apply for”, please indicate which project you are applying for
(title from the above list of PhD projects).
You may apply prior to obtaining your master's degree but cannot begin before having received it.
Incomplete applications will not be considered. 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 Department of Applied Mathematics and Computer Science (DTU Compute) is one of the 20 departments at DTU and employs approximately 400 people in total. The study will take place in the Section for Visual Computing, one of the 11 research sections at DTU Compute. The section for Visual Computing employs 12 permanent faculty members and a total number of employees around 45 including PhDs and postdocs. Research in the section concerns image analysis and computer graphics applied to different areas including computer vision, medicine, materials science, and manufacturing.
Medical image analysis is a core focus area for the group and central to teaching, project collaboration with external partners, and research. Deep learning is central to this research proposal, and several research projects in the section are based on deep learning for medical image analysis, and most of the employees in the section use deep learning in their research. This makes a strong research environment with extensive knowledge and experience that significantly will support the proposed project. The section has established a close collaboration with the heart center and the center for diagnostic radiology at Rigshospitalet. A deep learning computing setup and office space is established at Rigshospitalet, where students and employees from DTU Compute collaborate with the staff at Rigshospitalet.
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 13,500 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.
INFORMATIONER OM STILLINGEN:
- Arbejdspladsen ligger i:
Lyngby-Taarbæk Kommune
-Virksomheden tilbyder:
-Arbejdsgiver:
Danmarks Tekniske Universitet, Anker Engelunds Vej, 2800 Kongens Lyngby
-Ansøgning:
Ansøgningsfrist: 15-11-2023; - ansøgningsfristen er overskredet
Se mere her: https://job.jobnet.dk/CV/FindWork/Details/5932625
