Postdoc in Modal-based learning f
Denne stilling er desværre ikke længere ledig.
Se alle ledige stillinger
København Ø
Department of Computer Science
Faculty of Science
University of Copenhagen
The Department of Computer Science invites applications for a unique two-year postdoctoral position with possibility for further extension. The successful candidate will engage in developing innovative learning based techniques for automated generation of biomechanical models for in-silico testing and development of medical devices. This exciting opportunity focuses on two key challenges. The first is to create methods for an automated and efficient segmentation of computed tomography images of the abdomen region and converting these to computational meshes. This may involve designing an approach for estimating this tissue strucures such as mucosa walls by combining image data with semantics during segmentation. The generated models will empower simulation-based learning to understand how to navigate the interior of the human body. The second significant challenge is to develop colour and texture data-driven techniques for synthetic video rendering of the interior human body. The intent is to empower simulation-based learning approaches for navigation to use visual observations in real-life endoscopes. The role demands a strong foundation in medical image analysis, geometry processing, and a keen interest in applying machine learning techniques to solve these complex and critical medical challenges.
The successful candidate for this postdoctoral position will be joining a multidisciplinary and collaborative team at Department of Computer Science, renowned for its cutting-edge research in medical imaging and simulation technologies. This team is comprised of experts in various fields, creating a rich environment for innovation and interdisciplinary learning. The team operates in a highly collaborative environment, encouraging the exchange of ideas and expertise. Regular meetings and workshops are conducted to discuss progress, challenges, and strategies, ensuring a cohesive and focused approach to the project goals. Senior members of the team, including leading researchers and professors, provide mentorship and guidance. They are committed to nurturing the next generation of scientists, offering support in both research and career development. The team is part of a wider network of researchers and professionals, both within and outside the institution. This global network provides opportunities for academic and industrial collaborations wihtin France, Germany and Spain, sharing best practices, and staying abreast of the latest developments in the scope of the project. The team is driven by a shared goal to make significant contributions to the field of medical simulations and patient care. There is a strong emphasis on creating practical, innovative solutions that can be translated into real-world applications.
The candidate will be expected to contribute significantly to the research objectives, demonstrating both technical expertise and collaborative skills. Key performance expectations include:
Research at the Core
The ultimate goal is to make a significant contribution to the field of medical simulation and patient care. This includes producing impactful research outputs, such as publications in high-quality journals, and potentially developing technologies or methodologies that can be applied in real-world settings.
Career Growth While contributing to the project, the candidate is also expected to focus on their professional growth, taking advantage of mentorship opportunities, networking, and other resources provided by the institution.
Collaboration is Central
Given the interdisciplinary nature of the team, the candidate must excel in collaborative environments. This includes actively participating in team discussions, sharing knowledge and expertise, and contributing to a positive and productive team dynamic.
Communication in Focus
The candidate must be able to clearly and effectively present research findings to both technical and non-technical audiences, including writing high-quality research papers and presenting at conferences.
Domain knowledge
The domain for this biomechanical population generation project will be abdominal CT scans of humans from which colon segmentations need to be derived. Hence, we require previous knowledge of segmenting abdominal CT scan as well as knowledge about the physiological properties of the human colon.
Qualifications:
The postdoc’s duties will include research within numerical physics simulation. The post may also include performance of other duties.
Further information on the Department is linked at http://www.science.ku.dk/english/about-the-faculty/organisation/. Inquiries about the position can be made to professor Kenny Erleben, [email protected].
The position is open from 1st of August 2024or as soon as possible thereafter.
The University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background.
Terms of employment
The position is covered by the Memorandum on Job Structure for Academic Staff.
Terms of appointment and payment accord to the agreement between the Ministry of Finance and The Danish Confederation of Professional Associations on Academics in the State.
Negotiation for salary supplement is possible.
The application, in English, must be submitted electronically by clicking APPLY NOW below.
Please include
The deadline for applications is 30 May 2024, 23:59 CEST.
After the expiry of the deadline for applications, the authorized recruitment manager selects applicants for assessment on the advice of the Interview Committee.
You can read about the recruitment process at http://employment.ku.dk/faculty/recruitment-process/.
Interviews will be held in June 2024.
Kilde: Jobnet.dk
Faculty of Science
University of Copenhagen
The Department of Computer Science invites applications for a unique two-year postdoctoral position with possibility for further extension. The successful candidate will engage in developing innovative learning based techniques for automated generation of biomechanical models for in-silico testing and development of medical devices. This exciting opportunity focuses on two key challenges. The first is to create methods for an automated and efficient segmentation of computed tomography images of the abdomen region and converting these to computational meshes. This may involve designing an approach for estimating this tissue strucures such as mucosa walls by combining image data with semantics during segmentation. The generated models will empower simulation-based learning to understand how to navigate the interior of the human body. The second significant challenge is to develop colour and texture data-driven techniques for synthetic video rendering of the interior human body. The intent is to empower simulation-based learning approaches for navigation to use visual observations in real-life endoscopes. The role demands a strong foundation in medical image analysis, geometry processing, and a keen interest in applying machine learning techniques to solve these complex and critical medical challenges.
The successful candidate for this postdoctoral position will be joining a multidisciplinary and collaborative team at Department of Computer Science, renowned for its cutting-edge research in medical imaging and simulation technologies. This team is comprised of experts in various fields, creating a rich environment for innovation and interdisciplinary learning. The team operates in a highly collaborative environment, encouraging the exchange of ideas and expertise. Regular meetings and workshops are conducted to discuss progress, challenges, and strategies, ensuring a cohesive and focused approach to the project goals. Senior members of the team, including leading researchers and professors, provide mentorship and guidance. They are committed to nurturing the next generation of scientists, offering support in both research and career development. The team is part of a wider network of researchers and professionals, both within and outside the institution. This global network provides opportunities for academic and industrial collaborations wihtin France, Germany and Spain, sharing best practices, and staying abreast of the latest developments in the scope of the project. The team is driven by a shared goal to make significant contributions to the field of medical simulations and patient care. There is a strong emphasis on creating practical, innovative solutions that can be translated into real-world applications.
The candidate will be expected to contribute significantly to the research objectives, demonstrating both technical expertise and collaborative skills. Key performance expectations include:
Research at the Core
The ultimate goal is to make a significant contribution to the field of medical simulation and patient care. This includes producing impactful research outputs, such as publications in high-quality journals, and potentially developing technologies or methodologies that can be applied in real-world settings.
Career Growth While contributing to the project, the candidate is also expected to focus on their professional growth, taking advantage of mentorship opportunities, networking, and other resources provided by the institution.
Collaboration is Central
Given the interdisciplinary nature of the team, the candidate must excel in collaborative environments. This includes actively participating in team discussions, sharing knowledge and expertise, and contributing to a positive and productive team dynamic.
Communication in Focus
The candidate must be able to clearly and effectively present research findings to both technical and non-technical audiences, including writing high-quality research papers and presenting at conferences.
Domain knowledge
The domain for this biomechanical population generation project will be abdominal CT scans of humans from which colon segmentations need to be derived. Hence, we require previous knowledge of segmenting abdominal CT scan as well as knowledge about the physiological properties of the human colon.
Qualifications:
- PhD in a relevant field such as Biomedical Engineering, Computer Science, Mechanical Engineering, Applied math, Robotics or similar.
- Strong foundation in biomechanical modeling, simulation, and/or machine learning.
- Domain knowledge in abdominal CT and physiological properties of the human colon
- Experience with numerical optimization algorithms.
- Proficiency in scientific computing programming.
The postdoc’s duties will include research within numerical physics simulation. The post may also include performance of other duties.
Further information on the Department is linked at http://www.science.ku.dk/english/about-the-faculty/organisation/. Inquiries about the position can be made to professor Kenny Erleben, [email protected].
The position is open from 1st of August 2024or as soon as possible thereafter.
The University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background.
Terms of employment
The position is covered by the Memorandum on Job Structure for Academic Staff.
Terms of appointment and payment accord to the agreement between the Ministry of Finance and The Danish Confederation of Professional Associations on Academics in the State.
Negotiation for salary supplement is possible.
The application, in English, must be submitted electronically by clicking APPLY NOW below.
Please include
- Curriculum vitae
- Diplomas (Master, Bachelor, and PhD degree or equivalent)
- Research plan – description of current and future research plans
- Complete publication list
- Separate reprints of 3 particularly relevant papers
The deadline for applications is 30 May 2024, 23:59 CEST.
After the expiry of the deadline for applications, the authorized recruitment manager selects applicants for assessment on the advice of the Interview Committee.
You can read about the recruitment process at http://employment.ku.dk/faculty/recruitment-process/.
Interviews will be held in June 2024.
Kilde: Jobnet.dk
Information og data
Denne ledige stilling har jobtypen "Forsker", og befinder sig i kategorien "Sundhed og forskning".
Arbejdsstedet er beliggende i København Ø.
Jobbet er oprettet på vores service den 15.5.2024, men kan have været deaktiveret og genaktiveret igen.
Dagligt opdateret: Dette job opdateres dagligt ud fra jobudbyderens hjemmeside via vores søgemaskineteknologi og er aktivt lige nu.
- Forsker
- København Ø
- Torsdag den 30. maj 2024
Lignende jobs
-
Post Doc in Historical Geobiology using high-strat...
The Dahl Group at the Section for Geology is offering a Post Doc position for an excellent, ambitious, and highly motivated candidate with background in experimental sedimentary geochemistry and re..Få mere info- Forsker
- København K
-
Postdoc of Global Nutrition and Health
Få mere info- Forsker
- Frederiksberg
-
Adjunkt eller lektor til fysioterapeutuddannelsen
Vores ambition er at uddanne fysioterapeuter, som med ansvarlighed og stærk faglighed kan træde ud og repræsentere professionen på bedste vis i samfundet. Vil du være med til at skabe forpligtende .Få mere info- Forsker
- København N
-
PhD fellowship in plant proteins and data modellin...
Department of Food Science invites applicants for a PhD fellowship in Synergizing chemistry and data science to enhance plant-based food development.Start date is 1 February 2025 or as soon as .Få mere info- Forsker
- København
Statistik over udbudte jobs som forskere i København Ø
Herunder ser du udviklingen i udbudte forsker i København Ø over tid. Bemærk at jobs der ikke har en bestemt geografi ikke er medtaget i tabellen. I den første kolonne ser du datoen. I den næste kolonne ser du det samlede antal forskere.
Se flere statistikker her:
Statistik over udbudte forskere i København Ø over tid
| Dato | Alle jobs som forskere |
|---|---|
| 26. november 2024 | 13 |
| 25. november 2024 | 14 |
| 24. november 2024 | 14 |
| 23. november 2024 | 14 |
| 22. november 2024 | 14 |
| 21. november 2024 | 14 |
| 20. november 2024 | 13 |
| 19. november 2024 | 13 |
| 18. november 2024 | 15 |
| 17. november 2024 | 15 |
| 16. november 2024 | 15 |
| 15. november 2024 | 13 |
| 14. november 2024 | 12 |
| 13. november 2024 | 12 |
| 12. november 2024 | 12 |
| 11. november 2024 | 12 |
| 10. november 2024 | 14 |
| 9. november 2024 | 14 |
| 8. november 2024 | 14 |
| 7. november 2024 | 13 |
| 6. november 2024 | 13 |
| 5. november 2024 | 13 |
| 4. november 2024 | 13 |
| 3. november 2024 | 14 |
| 2. november 2024 | 14 |
| 1. november 2024 | 17 |
| 31. oktober 2024 | 18 |
| 30. oktober 2024 | 18 |
| 29. oktober 2024 | 17 |
| 28. oktober 2024 | 15 |
| 27. oktober 2024 | 18 |